Working papers and publications
We have a long tradition of conducting world-class research. Our working papers series has been very influential and continues to advance the discipline. Nearly all of our working papers appear in print in leading journals in econometrics and statistics.
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2023
Working Papers
Brett G. Mitchell, Andrew Stewardson, Lucille Kerr, John K. Ferguson, Stephanie Curtis, Lucy Busija, Kirsty Graham, Michael J. Lydeamore and Philip L. Russo
(2023). The incidence of positive bloodstream and urine cultures in five Australian hospitals during the COVID-19 pandemic ( Department of Econometrics and Business Statistics Working Paper Series 04/23).Chaohua Donga, Jiti Gao, Bin Peng and Yundong Tu
(2023). Robust M–Estimation for Additive Single–Index Cointegrating Time Series Models ( Department of Econometrics and Business Statistics Working Paper Series 02/23).D.S. Poskitt and Xueyan Zhao
(2023). Bootstrap Hausdoff Confidence Regions for Average Treatment Effect Identified Sets ( Department of Econometrics and Business Statistics Working Paper Series 09/23).Daniele Girolimetto, George Athanasopoulos, Tommaso Di Fonzo, and Rob J Hyndman
(2023). Cross-temporal Probabilistic Forecast Reconciliation ( Department of Econometrics and Business Statistics Working Paper Series 06/23).David T. Frazier, Ryan Covey, Gael M. Martin, and Donald Poskitt
(2023). Solving the Forecast Combination Puzzle ( Department of Econometrics and Business Statistics Working Paper Series 18/23).Degui Li, Bin Peng, Songqiao Tang, Weibiao Wu
(2023). Inference of Grouped Time-Varying Network Vector Autoregression Models ( Department of Econometrics and Business Statistics Working Paper Series 05/23).Gael M. Martin, David T. Frazier, Ruben Loaiza-Maya, Florian Huber, Gary Koop, John Maheu, Didier Nibbering and Anastasios Panagiotelis
(2023). Bayesian Forecasting in the 21st Century: A Modern Review ( Department of Econometrics and Business Statistics Working Paper Series 01/23).George Athanasopoulos, Rob J Hyndman, Nikolaos Kouretzes and Anastasios Panagiotelis
(2023). Forecast reconciliation: A Review ( Department of Econometrics and Business Statistics Working Paper Series 08/23).Heather Anderson, Jiti Gao, Farshid Vahid, Wei Wei, and Yang Yang
(2023). Does Climate Sensitivity Differ Across Regions? A Varying-Coefficient Approach ( Department of Econometrics and Business Statistics Working Paper Series 07/23).Jiti Gao, Bin Peng and Yanrong Yang
(2023). A Localised Neural network with Dependent Data: Estimation and Inference ( Department of Econometrics and Business Statistics Working Paper Series 15/23).Jiti Gao, Bin Peng and Yayi Yan
(2023). Higher-Order Expansions and Inference for Panel Data Models ( Department of Econometrics and Business Statistics Working Paper Series 14/23).Jiti Gao, Bin Peng and, Yayi Yan
(2023). Time-Varying Vector Error Correction Modules: Estimation and Inference ( Department of Econometrics and Business Statistics Working Paper Series 11/23).Puwasala Gamakumara, Edgar Santos-Fernandez, Priyanga Dilini Talagala, Rob J Hyndman, Kerrie Mengersen, and Catherine Leigh
(2023). Conditional normalization in time series analysis ( Department of Econometrics and Business Statistics Working Paper Series 10/23).Raffaele Mattera, George Athanasopoulos, Rob J Hyndman
(2023). Improving Out-of-Sample Forecasts of Stock Price Indexes with Forecast Reconciliation and Clustering ( Department of Econometrics and Business Statistics Working Paper Series 17/23).Ryan Thompson, Catherine S. Forbes, Steven N. MacEachern and Mario Peruggia
(2023). Familial Inference: Tests for hypotheses on a family of centres ( Department of Econometrics and Business Statistics Working Paper Series 16/23).Thao P. Le, Isobel Abell, Eamon Conway, Patricia T. Campbell, Alexandra B. Hogan, Michael J. Lydeamore, Jodie McVernon, Ivo Mueller, Camelia R. Walker, Christopher M. Baker
(2023). Modelling the impact of hybrid immunity on future COVID-19 epidemic waves ( Department of Econometrics and Business Statistics Working Paper Series 03/23).Yu Bai, Massimiliano Marcellino and George Kapetanios
(2023). Mean Group Instrumental Variable Estimation of Time-Varying Large Heterogenous Panels with Endogenous Regressors ( Department of Econometrics and Business Statistics Working Paper Series 13/23).2022
Working Papers
Christian Cox, Akanksha Negi and Digvijay Negi
(2022). Risk-Sharing Tests with Network Transaction Costs ( Department of Econometrics and Business Statistics Working Paper Series 05/22).David T. Frazier, Ruben Loaiza-Maya and Gael M. Martin
(2022). Variational Bayes in State Space Models: Inferential and Predictive Accuracy ( Department of Econometrics and Business Statistics Working Paper Series 01/22).Difang Huang, Jiti Gao and Tatsushi Oka
(2022). Semiparametric Single-Index Estimation for Average Treatment Effects ( Department of Econometrics and Business Statistics Working Paper Series 10/22).Gael M. Martin, David T. Frazier and Christian P. Robert
(2022). Computing Bayes: From Then 'Til Now ( Department of Econometrics and Business Statistics Working Paper Series 14/22).Guohua Feng, Jiti Gao and Bin Peng
(2022). Multi-Level Panel Data Models: Estimation and Empirical Analysis ( Department of Econometrics and Business Statistics Working Paper Series 04/22).Heather M. Anderson, Jiti Gao, Guido Turnip, Farshid Vahid and Wei Wei
(2022). Estimating the Effect of an EU-ETS Type Scheme in Australia Using a Synthetic Treatment Approach ( Department of Econometrics and Business Statistics Working Paper Series 12/22).Jiti Gao, Bin Peng and Yayi Yan
(2022). A Simple Bootstrap Method for Panel Data Inferences ( Department of Econometrics and Business Statistics Working Paper Series 07/22).Jiti Gao, Bin Peng and Yayi Yan
(2022). Nonparametric Estimation and Testing for Time- Varying VAR models ( Department of Econometrics and Business Statistics Working Paper Series 03/22).Jiti Gao, Bin Peng, Wei Biao Wu and Yayi Yan
(2022). Time-Varying Multivariate Causal Processes ( Department of Econometrics and Business Statistics Working Paper Series 08/22).Jiti Gao, Oliver Linton and Bin Peng
(2022). A Nonparametric Panel Model for Climate Data with Seasonal and Spatial Variation ( Department of Econometrics and Business Statistics Working Paper Series 09/22).Ruofan Xu, Jiti Gao, Tatsushi Oka and Yoon-Jae Whang
(2022). Estimation of Heterogeneous Treatment Effects Using Quantile Regression with Interactive Fixed Effects ( Department of Econometrics and Business Statistics Working Paper Series 13/22).Ryan Thompson, Catherine S. Forbes, Steven N. MacEachern, Mario Peruggia
(2022). Familial Inference ( Department of Econometrics and Business Statistics Working Paper Series 02/22).Ryan Zischke, Gael M. Martin, David T. Frazier and D. S. Poskitt
(2022). The Impact of Sampling Variability on Estimated Combinations of Distributional Forecasts ( Department of Econometrics and Business Statistics Working Paper Series 06/22).Tingting Cheng, Chaohua Dong, Jiti Gao and Oliver Linton
(2022). GMM Estimation for High-Dimensional Panel Data Models ( Department of Econometrics and Business Statistics Working Paper Series 11/22).2021
Working Papers
Athanasopoulos, G., Hyndman, Rob J., Kourentzes, N., and O'Hara-Wild, M.
(2021). Probabilistic forecasts using expert judgement: the road to recovery from COVID-19 ( Department of Econometrics and Business Statistics Working Paper Series 01/2021).Athanasopoulos, George and Kourentzes, Nikolaos
(2021). On the evaluation of hierarchical forecasts ( Department of Econometrics and Business Statistics Working Paper Series 10/2021).Berger, Tino, Richter, Julia and Wong, Benjamin
(2021). A Unified Approach for Jointly Estimating the Business and Financial Cycle, and the Role of Financial Factors ( Department of Econometrics and Business Statistics Working Paper Series 04/2021).Bodha Hannadige, Sium, Gao, Jiti, Silvapulle, Mervyn J. and Silvapulle, Param
(2021). Time Series Forecasting using a Mixture of Stationary and Nonstationary Predictors ( Department of Econometrics and Business Statistics Working Paper Series 06/2021).Cheng, Fan, Hyndman, Rob J. and Panagiotelis, Anastasios
(2021). Manifold learning with approximate nearest neighbors ( Department of Econometrics and Business Statistics Working Paper Series 03/2021).Chirakijja, Janjala, Jayachandran, Seema and Ong, Pinchuan
(2021). Inexpensive Heating Reduces Winter Mortality ( Department of Econometrics and Business Statistics Working Paper Series 09/2021).Dong, Chaohua, Gao, Jiti, Peng, Bin and Tu, Yundong
(2021). Multiple–index Nonstationary Time Series Models: Robust Estimation Theory and Practice ( Department of Econometrics and Business Statistics Working Paper Series 18/2021).Feng, Guohua, Gao, Jiti and Peng, Bin
(2021). Productivity Convergence in Manufacturing: a Hierarchical Panel Data Approach ( Department of Econometrics and Business Statistics Working Paper Series 16/2021).Frazier, David T., Loaiza-Maya, Ruben, Martin, Gael M. and Koo, Bonsoo
(2021). Loss-Based Variational Bayes Prediction ( Department of Econometrics and Business Statistics Working Paper Series 08/2021).Gao, Jiti, Peng, Bin and Yan, Yayi
(2021). Parameter Stability Testing for Multivariate Dynamic Time-Varying Models ( Department of Econometrics and Business Statistics Working Paper Series 11/2021).Griffiths, William, Chotikapanich, Duangkamon and Hajargasht, Gholamreza
(2021). A Note on Inequality Measures for Mixtures of Double Pareto-Lognormal Distributions ( Department of Econometrics and Business Statistics Working Paper Series 14/2021).Gunawan, David, Griffiths, William and Chotikapanich, Duangkamon
(2021). Comparisons of Australian Mental Health Distributions ( Department of Econometrics and Business Statistics Working Paper Series 12/2021).Gunawan, David, Griffiths, William and Chotikapanich, Duangkamon
(2021). Inequality in Education: A Comparison of Australian Indigenous and Nonindigenous Populations ( Department of Econometrics and Business Statistics Working Paper Series 13/2021).Gupta, Sayani, Hyndman, Rob J. and Cook, Dianne
(2021). Detecting distributional differences between temporal granularities for exploratory time series analysis ( Department of Econometrics and Business Statistics Working Paper Series 20/2021).Kandanaarachchi, Sevvandi and Hyndman, Rob J.
(2021). Leave-one-out kernel density estimates for outlier detection ( Department of Econometrics and Business Statistics Working Paper Series 02/2021).Liang, Xuan, Gao, Jiti & Gong, Xiaodong
(2021). Semiparametric Spatial Autoregressive Panel Data Model with Fixed Effects and Time-Varying Coefficients ( Department of Econometrics and Business Statistics Working Paper Series 05/2021).Mao, Yufeng, Peng, Bin, Silvapulle, Mervyn, Silvapulle, Param and Yang, Yanrong
(2021). Decomposition of Bilateral Trade Flows Using a Three-Dimensional Panel Data Model ( Department of Econometrics and Business Statistics Working Paper Series 07/2021).Martin, Gael M., Frazier, David T. and Robert, Christian P.
(2021). Approximating Bayes in the 21st Century ( Department of Econometrics and Business Statistics Working Paper Series 24/2021).Nibbering, Didier, van Buuren, Coos and Wei, Wei
(2021). Real options valuation of wind energy based on the empirical production uncertainty ( Department of Econometrics and Business Statistics Working Paper Series 19/2021).Peng, Bin, Su, Liangju, Westerlund, Joakim and Yang, Yanrong
(2021). Interactive Effects Panel Data Models with General Factors and Regressors ( Department of Econometrics and Business Statistics Working Paper Series 23/2021).Pourkhanali, Armin, Keith, Jonathan and Zhang, Xibin
(2021). Conditional Heteroscedasticity Models with Time-Varying Parameters: Estimation and Asymptotics ( Department of Econometrics and Business Statistics Working Paper Series 15/2021).Yan, Yayi, Gao, Jiti and Peng, Bin
(2021). Asymptotics for Time-Varying Vector MA (∞) Processes ( Department of Econometrics and Business Statistics Working Paper Series 22/2021).Yan, Yayi, Gao, Jiti and Peng, Bin
(2021). On Time-Varying VAR models: Estimation, Testing and Impulse Response Analysis ( Department of Econometrics and Business Statistics Working Paper Series 17/2021).Zhang, Lina, Frazier, David T., Poskitt, D.S. and Zhao, Xueyan
(2021). Decomposing Identification Gains and Evaluating Instrument Identification Power for Partially Identified Average Treatment Effects ( Department of Econometrics and Business Statistics Working Paper Series 21/2021).2020
Working Papers
Anderson, Heather, Caggiano, Giovanni, Vahid, Farshid and Wong, Benjamin
(2020). Sectoral Employment Dynamics in Australia ( Department of Econometrics and Business Statistics Working Paper Series 20/2020).Athanasopoulos, G. and Kourentzes, N.
(2020). On the evaluation of hierarchical forecasts ( Department of Econometrics and Business Statistics Working Paper Series 02/2020).Bailey, N., Kapetanios, G. and Pesaran, M. H.
(2020). Measurement of Factor Strength: Theory and Practice ( Department of Econometrics and Business Statistics Working Paper Series 07/2020).Bailey, Natalia, Hochman, Zvi, Mao, Yufeng, Silvapulle, Mervyn and Silvapulle, Param
(2020). Statistical modelling and forecast evaluation of the impact of extreme temperatures on wheat crops in North Western Victoria ( Department of Econometrics and Business Statistics Working Paper Series 18/2020).Bodha Hannadige, Sium, Gao, Jiti, Silvapulle, Mervyn J. and Silvapulle, Param
(2020). Forecasting a Nonstationary Time Series with a Mixture of Stationary and Nonstationary Factors as Predictors ( Department of Econometrics and Business Statistics Working Paper Series 19/2020).Calvi, Rossella, Penglase, Jacob, Tommasi, Denni and Wolf, Alexander
(2020). The More the Poorer? Resource Sharing and Scale Economies in Large Families ( Department of Econometrics and Business Statistics Working Paper Series 46/2020).Cui, Guowei, Sarafidis, Vasilis and Yamagata, Takashi
(2020). IV Estimation of Spatial Dynamic Panels with Interactive Effects: Large Sample Theory and an Application on Bank Attitude Toward Risk ( Department of Econometrics and Business Statistics Working Paper Series 11/2020).Dong, Chaohua, Gao, Jiti, Linton, Oliver and Peng, Bin
(2020). On Time Trend of COVID-19: A Panel Data Study ( Department of Econometrics and Business Statistics Working Paper Series 22/2020).Eric Hillebrand, Manuel Lukas and Wei Wei
(2020). Bagging Weak Predictors ( Department of Econometrics and Business Statistics Working Paper Series 16/2020).Frazier, David T. and Koo, Bonsoo
(2020). Indirect Inference for Locally Stationary Models ( Department of Econometrics and Business Statistics Working Paper Series 30/2020).Gaggero, Alessio and Tommasi, Denni
(2020). Time of Day, Cognitive Tasks and Efficiency Gains ( Department of Econometrics and Business Statistics Working Paper Series 38/2020).Gao, Jiti, Liu, Fei and Peng, Bin
(2020). Binary Response Models for Heterogeneous Panel Data with Interactive Fixed Effects ( Department of Econometrics and Business Statistics Working Paper Series 44/2020).Gao, Jiti, Peng, Bin and Smyth, Russell
(2020). On Income and Price Elasticities for Energy Demand: A Panel Data Study ( Department of Econometrics and Business Statistics Working Paper Series 28/2020).Gupta, Sayani, Hyndman, Rob J., Cook, Dianne and Unwin, Antony
(2020). Visualizing probability distributions across bivariate cyclic temporal granularities ( Department of Econometrics and Business Statistics Working Paper Series 35/2020).Harris, D., Kew, H. and Taylor, A. M. R.
(2020). Level Shift Estimation in the Presence of Non-stationary Volatility with an Application to the Unit Root Testing Problem ( Department of Econometrics and Business Statistics Working Paper Series 08/2020).He, Yi, Jaidee, Sombut and Gao, Jiti
(2020). Most Powerful Test against High Dimensional Free Alternatives ( Department of Econometrics and Business Statistics Working Paper Series 13/2020).Hyndman, Rob J., Zeng, Yijun and Shang, Han Lin
(2020). Forecasting the old-age dependency ratio to determine a sustainable pension age ( Department of Econometrics and Business Statistics Working Paper Series 31/2020).Juodis, Arturas and Sarafidis, Vasilis
(2020). A Linear Estimator for Factor- Augmented Fixed-T Panels with Endogenous Regressors ( Department of Econometrics and Business Statistics Working Paper Series 05/2020).Juodis, Artūras, Karavias, Yiannis and Sarafidis, Vasilis
(2020). A Homogeneous Approach to Testing for Granger Non-Causality in Heterogeneous Panels ( Department of Econometrics and Business Statistics Working Paper Series 32/2020).Koo, Bonsoo, La Vecchia, Davide and Linton, Oliver
(2020). Estimation of a nonparametric model for bond prices from cross-section and time series information ( Department of Econometrics and Business Statistics Working Paper Series 04/2020).Koo, Bonsoo, Pantelous, Athanasios A. and Wang, Yunxiao
(2020). Novel utility-based life cycle models to optimise income in retirement in the presence of heterogeneous preferences ( Department of Econometrics and Business Statistics Working Paper Series 21/2020).Laa, Ursula, Cook, Dianne and Lee, Stuart
(2020). Burning sage: Reversing the curse of dimensionality in the visualization of high-dimensional dataf ( Department of Econometrics and Business Statistics Working Paper Series 36/2020).Laa, Ursula, Cook, Dianne, Buja, Andreas and Valencia, German
(2020). Hole or grain? A Section Pursuit Index for Finding Hidden Structure in Multiple Dimensions ( Department of Econometrics and Business Statistics Working Paper Series 17/2020).Litvinova, Svetlana and Silvapulle, Mervyn J.
(2020). Consistency of full-sample bootstrap for estimating high-quantile, tail probability, and tail index ( Department of Econometrics and Business Statistics Working Paper Series 15/2020).Liu, Fei, Gao, Jiti and Yang, Yanrong
(2020). Time-Varying Panel Data Models with an Additive Factor Structure ( Department of Econometrics and Business Statistics Working Paper Series 42/2020).Loaiza-Maya, R., Martin, Gael M. and Frazier, David T.
(2020). Focused Bayesian Prediction ( Department of Econometrics and Business Statistics Working Paper Series 01/2020).Loaiza-Maya, Ruben and Nibbering, Didier
(2020). Scalable Bayesian estimation in the multinomial probit model ( Department of Econometrics and Business Statistics Working Paper Series 25/2020).Maneesoonthorn, Worapree, Martin, Gael M. and Forbes, Catherine S.
(2020). High-Frequency JumpTests: Which Test Should We Use? ( Department of Econometrics and Business Statistics Working Paper Series 03/2020).Martin, Gael M., Frazier, David T. and Robert, Christian P.
(2020). Computing Bayes: Bayesian Computation from 1763 to the 21st Century ( Department of Econometrics and Business Statistics Working Paper Series 14/2020).Martin, Gael M., Loaiza-Maya, Rubén, Frazier, David T., Maneesoonthorn, Worapree
and Ramírez Hassan, Andrés
Montero-Manso, Pablo and Hyndman, Rob J
(2020). Principles and Algorithms for Forecasting Groups of Time Series: Locality and Globality ( Department of Econometrics and Business Statistics Working Paper Series 45/2020).Nath, H.B. and Brooks, R.D.
(2020). Investor-herding and risk-profiles: A State-Space model-based assessment ( Department of Econometrics and Business Statistics Working Paper Series 09/2020).Panagiotelis, Anastasios, Athanasopoulos, George, Gamakumara, Puwasala and Hyndman, Rob J.
(2020). Forecast reconciliation: A geometric view with new insights on bias correction ( Department of Econometrics and Business Statistics Working Paper Series 23/2020).Panagiotelis, Athanasios, Gamakumara, Puwasala, Athanasopoulos, George and Hyndman, Rob J.
(2020). Probabilistic Forecast Reconciliation: Properties, Evaluation and Score Optimisation ( Department of Econometrics and Business Statistics Working Paper Series 26/2020).Poskitt, D.S.
(2020). On GMM Inference: Partial Identification, Identification Strength, and Non-Standard Asymptotics ( Department of Econometrics and Business Statistics Working Paper Series 40/2020).Roach, Cameron, Hyndman, Rob and Ben Taieb, Souhaib
(2020). Nonlinear mixed effects models for time series forecasting of smart meter demand ( Department of Econometrics and Business Statistics Working Paper Series 41/2020).Rostami-Tabar, Bahman, Ali, Mohammad M., Hong, Tao, Hyndman, Rob J., Porter,
Michael D. and Syntetos, Aris
Sarafidis, Vasilis and Wansbeek, Tom
(2020). Celebrating 40 Years of Panel Data Analysis: Past, Present and Future ( Department of Econometrics and Business Statistics Working Paper Series 06/2020).Tierney, Nicholas John, Cook, Dianne and Prvan, Tania
(2020). brolgar: An R package to BRowse Over Longitudinal Data Graphically and Analytically in R ( Department of Econometrics and Business Statistics Working Paper Series 43/2020).Tomasetti, Nathaniel, Forbes, Catherine S. and Panagiotelis, Anastasios
(2020). Updating Variational Bayes: Fast sequential posterior inference ( Department of Econometrics and Business Statistics Working Paper Series 27/2020).Tommasi, Denni and Zhang, Lina
(2020). Bounding Program Benefits When Participation is Misreported ( Department of Econometrics and Business Statistics Working Paper Series 24/2020).Wang, Xiaoqian, Kang, Yanfei, Hyndman, Rob J and Li, Feng
(2020). Distributed ARIMA Models for Ultra-long Time Series ( Department of Econometrics and Business Statistics Working Paper Series 29/2020).Wei, Wei and Lunde, Asger
(2020). Identifying risk factors and their premia: a study on electricity prices ( Department of Econometrics and Business Statistics Working Paper Series 10/2020).Yan, Yayi, Gao, Jiti and Peng, Bin
(2020). A Class of Time-Varying Vector Moving Average (∞) Models ( Department of Econometrics and Business Statistics Working Paper Series 39/2020).Zhang, Bo, Gao, Jiti and Pan, Guangming
(2020). Estimation and Testing for High-Dimensional Near Unit Root Time Series ( Department of Econometrics and Business Statistics Working Paper Series 12/2020).Zhang, Lina, Frazier, David T., Poskitt, D.S. and Zhao, Xueyan
(2020). Decomposing Identification Gains and Evaluating Instrument Identification Power for Partially Identified Average Treatment Effects ( Department of Econometrics and Business Statistics Working Paper Series 34/2020).2019
Working Papers
Ashouri, M., Hyndman, R. J. and Shmueli, G.
(2019). Fast forecast reconciliation using linear models ( Department of Econometrics and Business Statistics Working Paper Series 29/2019).Athanasopoulos, G., Gamakumara P., Panagiotelis. A., Hyndman, R. J., Affan, M.
(2019). Hierarchical Forecasting ( Department of Econometrics and Business Statistics Working Paper Series 02/19).Byrne, D.P., Imai, S., Jain, N., Sarafidis, V. & Hirukawa, M.
(2019). Identification and Estimation of Differentiated Products Models ( Department of Econometrics and Business Statistics Working Paper Series 33/2019).Casas, I., Gao, J., Peng, B. & Xie, S.
(2019). Time-Varying Income Elasticities of Healthcare Expenditure for the OECD and Eurozone ( Department of Econometrics and Business Statistics Working Paper Series 28/2019).Chen, L., Gao, J. and Vahid, F.
(2019). Global Temperatures and Greenhouse Gases: A Common Features Approach ( Department of Econometrics and Business Statistics Working Paper Series 23/2019).Cheng, T., Gao, J., & Linton, O.
(2019). Nonparametric Predictive Regressions for Stock Return Prediction ( Department of Econometrics and Business Statistics Working Paper Series 04/19).Feng G., Gao, J., & Peng, B.
(2019). An Integrated Panel Data Approach to Modelling Economic Growth ( Department of Econometrics and Business Statistics Working Paper Series 06/19).Florian Eckert, Rob J Hyndman and Anastasios Panagiotelis
(2019). Forecasting Swiss exports using Bayesian forecast reconciliation.pdf ( Department of Econometrics and Business Statistics Working Paper Series 14/2019).Forbes, J., Cook D., & Hyndman R. J.
(2019). Spatial modelling of the two-party preferred vote in Australian federal elections: 2001-2016 ( Department of Econometrics and Business Statistics Working Paper Series 08/19).Gao, J., Pan, G., Yanrong Y,. & Zhang, B.
(2019). Extent Pursuit for Cross-sectional Dependence in Large Panels ( Department of Econometrics and Business Statistics Working Paper Series 09/19).Hyndman, R. J.
(2019). A brief history of forecasting competitions ( Department of Econometrics and Business Statistics Working Paper Series 03/19).Kandanaarachchi, S. and Hyndman, R.J.
(2019). Dimension reduction for outlier detection using DOBIN ( Department of Econometrics and Business Statistics Working Paper Series 17/2019).King, Maxwell L., Zhang, Xibin & Akram, Muhammad
(2019). Hypothesis testing based on a vector of statistics ( Department of Econometrics and Business Statistics Working Paper Series 30/2019).Kourentzes, N. and Athanasopoulos, G.
(2019). Elucidate structure in intermittent demand series ( Department of Econometrics and Business Statistics Working Paper Series 27/19).Leung, P., Forbes, C.S., Martin, G.M. and McCabe, B.
(2019). Forecasting observables with particle filters: Any filter will do! ( Department of Econometrics and Business Statistics Working Paper Series 22/2019).Li, C., Poskitt, D. S., Windmeijer, F. & Zhao, X.
(2019). Binary Outcomes, OLS, 2SLS and IV Probit ( Department of Econometrics and Business Statistics Working Paper Series 05/2019).Liang, X., Gao, J. & Gong, X.
(2019). Time-Varying Coefficient Spatial Autoregressive Panel Data Model with Fixed Effects ( Department of Econometrics and Business Statistics Working Paper Series 26/2019).Liu, F., Gao, J. and Yang, Y.
(2019). Nonparametric Estimation in Panel Data Models with Heterogeneity and Time- Varyingness ( Department of Econometrics and Business Statistics Working Paper Series 24/2019).Nadarajah, K., Martin, Gael M., and Poskitt, D. S.
(2019). Optimal Bias Correction of the Logperiodogram Estimator of the Fractional Parameter: A Jackknife Approach ( Department of Econometrics and Business Statistics Working Paper Series 07/19).Nibbering, D.
(2019). A high-dimensional multinomial choice model ( Department of Econometrics and Business Statistics Working Paper Series 19/2019).Norkute, M., Sarafidis, V., Yamagata, T. & Cui, G.
(2019). Instrumental Variable Estimation of Dynamic Linear Panel Data Models with Defactored Regressors and a Multifactor Error Structure ( Department of Econometrics and Business Statistics Working Paper Series 32/2019).Panagiotelis, A., Gamakumara, P., Athanasopoulos, G. & Hyndman, R.J.
(2019). Forecast reconciliation A geometric view with new insights on bias correction ( Department of Econometrics and Business Statistics Working Paper Series 18/19).Talagala, P. D., Hyndman, R. J., Leigh, C., Mengersen, K., Smith-Miles, K.
(2019). A feature-based framework for detecting technical outliers in waterquality data from in situ sensors ( Department of Econometrics and Business Statistics Working Paper Series 01/19).Talagala, P.D., Hyndman, R. J. and Smith-Miles, K.
(2019). Anomaly Detection in High Dimensional Data ( Department of Econometrics and Business Statistics Working Paper Series 20/2019).Talagala, T.S., Li, F and Kang, Y.
(2019). FFORMPP: Feature-based Forecast Model Performance Prediction ( Department of Econometrics and Business Statistics Working Paper Series 21/2019).Tomasetti, N., Forbes, C., Panagiotelis, A.
(2019). Updating Variational Bayes: Fast sequential posterior inference ( Department of Econometrics and Business Statistics Working Paper Series 13/19).Wang, E., Cook, D., Hyndman, R. J.
(2019). Calendar-based graphics for visualizing people’s daily schedules ( Department of Econometrics and Business Statistics Working Paper Series 11/19).Wang, E., Cook, D., Hyndman, R.J.
(2019). A new tidy data structure to support exploration and modeling of temporal data ( Department of Econometrics and Business Statistics Working Paper Series 12/19).Wickramasuriya, S.L., Turlach, B.A. and Hyndman, R.J.
(2019). Optimal non-negative forecast reconciliation ( Department of Econometrics and Business Statistics Working Paper Series 15/2019).Zamani, A., Haghbin, H., Hashemi, M. and Hyndman, R.J.
(2019). Seasonal functional autoregressive models ( Department of Econometrics and Business Statistics Working Paper Series 16/2019).Zhang, B., Gao, J., and Pan, G.
(2019). A Near Unit Root Test for High- Dimensional Nonstationary Time Series ( Department of Econometrics and Business Statistics Working Paper Series 10/19).Zhang, B., Gao, J., Pan, G. & Yang, Y.
(2019). Spiked Eigenvalues of High- Dimensional Separable Sample Covariance Matrices ( Department of Econometrics and Business Statistics Working Paper Series 31/2019).Zhou, W., Gao, J., Harris, D and Kew, H.
(2019). Semiparametric Single-index Predictive Regression ( Department of Econometrics and Business Statistics Working Paper Series 25/2019).2018
Working Papers
Auld, T., & Linton, O.
(2018). The behaviour of betting and currency markets on the night of the EU referendum ( Department of Econometrics and Business Statistics Working Paper Series 10/18).Bailey, N., Kapetanios, G. & Hashem Pesaran, M.
(2018). Exponent of Cross-sectional Dependence for Residuals ( Department of Econometrics and Business Statistics Working Paper Series 13/18).Casas, I., Gao, J., & Xie, S.
(2018). Modelling Time-Varying Income Elasticities of Health Care Expenditure for the OECD ( Department of Econometrics and Business Statistics Working Paper Series 22/18).Cheng, T., Gao, J., & Yan, Y.
(2018). Regime Switching Panel Data Models with Interative Fixed Effects ( Department of Econometrics and Business Statistics Working Paper Series 21/18).Dong, C., Gao, J., & Peng, B.
(2018). Varying-Coefficient Panel Data Models with Partially Observed Factor Structure ( Department of Econometrics and Business Statistics Working Paper Series 1/18).Dong, C., Gao, J., & Peng, B.
(2018). Series Estimation for Single-Index Models under Constraints ( Department of Econometrics and Business Statistics Working Paper Series 5/18).Dong, C., Gao, J., & Linton, O.
(2018). High Dimensional Semiparametric Moment Restriction Models ( Department of Econometrics and Business Statistics Working Paper Series 23/18).Frazier, D.T., Maneesoonthorn, W., Martin, G.M., & McCabe, B.P.M.
(2018). Approximate Bayesian Forecasting ( Department of Econometrics and Business Statistics Working Paper Series 2/18).Gamakumara, P., Panagiotelis, A., Athanasopoulos, G., & Hyndman, R. J.
(2018). Probabilisitic Forecasts in Hierarchical Time Series ( Department of Econometrics and Business Statistics Working Paper Series 11/18).Gong, X., Gao, J., Liang, X., & Meng, X.
(2018). Inter-Regional Spillover and Intra-Regional Agglomeration Effects among Local Labour Markets in China ( Department of Econometrics and Business Statistics Working Paper Series 20/18).Kandanaarachchi S., Hyndman, R.J. & Smith-Miles, K.
(2018). Early classification of spatio-temporal events using time-varying models ( Department of Econometrics and Business Statistics Working Paper Series 25/18).Kandanaarachchi, S., Muñoz, M. A., Hyndman, R. J., & Smith-Miles, K.
(2018). On normalization and algorithm selection for unsupervised outlier detection ( Department of Econometrics and Business Statistics Working Paper Series 16/18).Kang, Y., Hyndman, R. J., & Li, F.
(2018). Efficient generation of time series with diverse and controllable characteristics ( Department of Econometrics and Business Statistics Working Paper Series 15/18).Kourentzes, N., & Athanasopoulos, G.
(2018). Cross-temporal coherent forecasts for Australian tourism ( Department of Econometrics and Business Statistics Working Paper Series 24/18).Li, C., Poskitt, D.S., & Zhao, X.
(2018). Bounds for Average Treatment Effect A Comparison of Non-parametric and Quasi Maximum Likelihood Estimators ( Department of Econometrics and Business Statistics Working Paper Series 26/18).Litvinova, S. & Silvapulle, M., J.
(2018). Bootstrapping tail statistics tail quantile process Hill estimator and confidence intervals for highquantiles of heavy tailed distributions ( Department of Econometrics and Business Statistics Working Paper Series 12/18).Maneesoonthorn, W., Martin, G. M., & Forbes, C. S.
(2018). Dynamic Price Jumps: the Performance of High Frequency Tests and Measures, and the Robustness of Inference ( Department of Econometrics and Business Statistics Working Paper Series 17/18).Martin, G. M., Nadarajah, K., & Poskitt, D. S.
(2018). Issues in the Estimation of Mis-Specified Models of Fractionally Integrated Processes ( Department of Econometrics and Business Statistics Working Paper Series 18/18).Montero-Manso, P., Athanasopoulos G., Hyndman, R. J., & Talagala, T. S.
(2018). FFORMA Feature-based Forecast Model Averaging ( Department of Econometrics and Business Statistics Working Paper Series 19/18).Oka, T., & Perron, P.
(2018). Testing for Common Breaks in a Multiple Equations System ( Department of Econometrics and Business Statistics Working Paper Series 3/18).Talagala, P. D., Hyndman, R. J., Smith-Miles, K., Kandanaarachchi, S. and Muñoz, M. A.
(2018). Anomaly Detection in Streaming Nonstationary Temporal Data ( Department of Econometrics and Business Statistics Working Paper Series 4/18).Talagala, T. S., Hyndman, R. J., and Athanasopoulos, G.
(2018). Meta-learning how to forecast time series ( Department of Econometrics and Business Statistics Working Paper Series 6/18).Tierney, N. & Cook, D.
(2018). Expanding tidy data principles to facilitate missing data exploration, visualization and assessment of imputations ( Department of Econometrics and Business Statistics Working Paper Series 14/18).Wang, H., Forbes, C. S., Fenech, J. P., & Vaz, J.
(2018). The determinants of bank loan recovery rates in good times and bad – new evidence ( Department of Econometrics and Business Statistics Working Paper Series 7/18).2017
Working Papers
Behlul, B., Panagiotelis, A., Athanasopoulos, G., Hyndman, R. J., & Vahid, F.
(2017). The Australian Macro Database: An online resource for macroeconomic research in Australia ( Department of Econometrics and Business Statistics Working Paper Series 01/17).Biqing C., and Jiti G.
(2017). A Simple Nonlinear Predictive Model for Stock Returns ( Department of Econometrics and Business Statistics Working Paper Series 18/17).Chaohua, D., Jiti G., and Oliver, L.
(2017). High Dimensional Semiparametric Moment Restriction Models ( Department of Econometrics and Business Statistics Working Paper Series 17/17).Cheng, T., Gao, J., & Phillips, P.C.B.
(2017). Bayesian Estimation Based on Summary Statistics: Double Asymptotics and Practice ( Department of Econometrics and Business Statistics Working Paper Series 04/17).Cheng, T., Gao, J., & Linton, O.
(2017). Multi-step non- and semi-parametric predictive regressions for short and long horizon stock return prediction ( Department of Econometrics and Business Statistics Working Paper Series 13/17).Frazier, D.T., Martin, G.M., Robert, C.P. and Rousseau, J.
(2017). Asymptotic Properties of Approximate Bayesian Computation ( Department of Econometrics and Business Statistics Working Paper Series 12/17).Gao, J, and Xia, K.
(2017). Heterogeneous panel data models with cross - sectional dependence ( Department of Econometrics and Business Statistics Working Paper Series 16/17).Gao, J., Linton, O., & Peng, B.
(2017). Inference-semiparametric-model-with-global-power-land-local-nonparametric-trends ( Department of Econometrics and Business Statistics Working Paper Series 10/17).Harris, D., Martin, G. M., Perera, I.,& Poskitt, D. S.
(2017). Construction-and-visualization-of-optimal-confidence-sets-for-frequentist-distributional-forecasts.pdf ( Department of Econometrics and Business Statistics Working Paper Series 09/17).Jiang, B., Athanasopoulos, G., Hyndman, R. J., Panagiotelis, A., & Vahid, F.,
(2017). Macroeconomic forecasting for Australia using a large number of predictors ( Department of Econometrics and Business Statistics Working Paper Series 02/17).Jiang, B., Yang, Y., Gao, J., & Hsiao, C.
(2017). Recursive Estimation in Large Panel Data Models: Theory and Practice ( Department of Econometrics and Business Statistics Working Paper Series 05/17).Lander, D, Gunawan D, Griffiths, W and Chotikapanich, D.
(2017). Bayesian assessment of lorenz and stochastic dominance ( Department of Econometrics and Business Statistics Working Paper Series 15/17).Li, D., Phillips, C. B. P., & Gao, J.
(2017). Kernel-based-inference- time-varying- coefficient-models-with-multiple-integrated-regressors ( Department of Econometrics and Business Statistics Working Paper Series 11/17).Liu, Z., Forbes, C., & Anderson, H.
(2017). Robust Bayesian Exponentially Tilted Empirical Likelihood Method ( Department of Econometrics and Business Statistics Working Paper Series 21/17).Maneesoonthorn, W., Martin, G.M., Forbes, C, S.
(2017). Dynamic Asset Price Jumps and the Performance of High Frequency Tests and Measures ( Department of Econometrics and Business Statistics Working Paper Series 14/17).Meng, Y., Zhao, X., Zhang, X., & Gao, J.
(2017). A Panel Data Analysis of Hospital Variations in Length of Stay for Hip Replacements: Private versus Public ( Department of Econometrics and Business Statistics Working Paper Series 20/17).Nithi S., Param S., and Jiti G.
(2017). Local logit regression for recovery rate ( Department of Econometrics and Business Statistics Working Paper Series 19/17).Shujie M., Linton O. and Gao, J.
(2017). Estimation and inference in Semiparametric Quantile Factor Models ( Department of Econometrics and Business Statistics Working Paper Series 08/17).Taieb, S., Taylor, J., & Hyndman, R.
(2017). Coherent Probabilistic Forecasts ( Department of Econometrics and Business Statistics Working Paper Series 03/17).Tan, B., Panagiotelis, A., & Athanasopoulos, G.
(2017). Bayesian Inference for a 1-Factor Copula Model ( Department of Econometrics and Business Statistics Working Paper Series 06/17).Wickramasuriya, S. L., Athanasopoulos, G., & Hyndman, R. J.
(2017). Optimal forecast reconciliation for hierarchical and grouped time series through trace minimization ( Department of Econometrics and Business Statistics Working Paper Series 22/17).Xiaodong, G., & Gao, J.
(2017). Nonparametric Kernel Estimation of the Impact of Tax Policy on the Demand for Private Health Insurance in Australia ( Department of Econometrics and Business Statistics Working Paper Series 07/17).2016
Working Papers
Cheng, T., Gao, J., & Peter CB Phillips (2016). A Frequency Approach to Bayesian Asymptotics ( Department of Econometrics and Business Statistics Working Paper Series 05/16).
Cheng, T., Gao, J., & Zhang, X (2016). Nonparametric Localized Bandwidth Selection for Kernel Density Estimation ( Department of Econometrics and Business Statistics Working Paper Series 07/16).
Creel, M.,Gao, J., Hong, H., & Kristensen,
(2016). Bayesian Indirect Inference and the ABC of GMM ( Department of Econometrics and Business Statistics Working Paper Series 01/16).D.T. Frazier., G.M. Martin., C.P. Robert., & J. Rousseau.
(2016). Asymptotic Properties of Approximate Bayesian Computation. ( Department of Econometrics and Business Statistics Working Paper Series 18/16).Dong, C., Gao, J., Tjøstheim, D., & Yin, J.
(2016). Specification Testing for Nonlinear Multivariate Cointegrating Regressions ( Department of Econometrics and Business Statistics Working Paper Series 14/16).Dong, Chaohua., Gao, Jiti & Peng, Bin.
(2016). Another Look at Single-Index Models Based on Series Estimation ( Department of Econometrics and Business Statistics Working Paper Series 19/16).
Feng, G., Gao, J., & Zhang, X (2016). Estimation of Technical Change and Price Elasticities: A Categorical Time-varying Coefficient Approach ( Department of Econometrics and Business Statistics Working Paper Series 02/16).
Gao, J., Pan, G., & Yang, Y.
(2016). Estimation of Structural Breaks in Large Panels with Cross-Sectional Dependence ( Department of Econometrics and Business Statistics Working Paper Series 12/16).Jiang, B., Panagiotelis, A., Athanasopoulos, G., Hyndman, R., & Vahid, F
(2016). Bayesian Rank Selection in Multivariate Regression ( Department of Econometrics and Business Statistics Working Paper Series 06/16).Kang, Y., Gong, X., Gao, J., & Qiu, P.
(2016). Error-in-Variables Jump Regression Using Local Clustering ( Department of Econometrics and Business Statistics Working Paper Series 13/16).Kang, Yanfei., Hyndman, R.J., & Smith-Miles, Kate.
(2016). Visualising Forecasting Algorithm Performance using Time Series Instance Spaces ( Department of Econometrics and Business Statistics Working Paper Series 10/16).Leung, P., Forbes, C. S., Martin, G. M., & McCabe, B
(2016). Data-driven Particle Filters for Particle Markov Chain Monte Carlo ( Department of Econometrics and Business Statistics Working Paper Series 17/16).Li, C., Poskitt, D.S., & Zhao, X.
(2016). The Bivariate Probit Model, Maximum Likelihood Estimation, Pseudo True Parameters and Partial Identification ( Department of Econometrics and Business Statistics Working Paper Series 16/16).Maneesoonthorn, W., Forbes, C. S., & Martin, G. M
(2016). Inference on Self-Exciting Jumps in Prices and Volatility using High Frequency Measures ( Department of Econometrics and Business Statistics Working Paper Series 08/16).Martin, G. M., McCabe, B. P. M., Frazier, D. T., Maneesoonthorn, W., & Robert, C. P
(2016). Auxiliary Likelihood-Based Approximate Bayesian Computation in State Space Models ( Department of Econometrics and Business Statistics Working Paper Series 09/16).Poskitt, D.S.
(2016). Singular Spectrum Analysis of Grenander Processes and Sequential Time Series Reconstruction ( Department of Econometrics and Business Statistics Working Paper Series 15/16).
Shang, L. H., & Hyndman, R. J (2016). Grouped functional time series forecasting: an application to age-specific mortality rates ( Department of Econometrics and Business Statistics Working Paper Series 04/16).
Tian, Fengping., Gao, Jiti., & Yang, Ke
(2016). A Quantile Regression Approach to Panel Data Analysis of Health Care Expenditure in OECD Countries ( Department of Econometrics and Business Statistics Working Paper Series 20/16).Url, T., Hyndman, R. J., & Dokumentov, A
(2016). Long-term forecasts of age-specific participation rates with functional data models ( Department of Econometrics and Business Statistics Working Paper Series 03/16).Zhang, Bo., Pan, Guangming., & Gao, Jiti.
(2016). CLT for Largest Eigenvalues and Unit Root Tests for High-Dimensional Nonstationary Time Series ( Department of Econometrics and Business Statistics Working Paper Series 11/16).2015
Working Papers
Athanasopoulos, G., Hyndman, R. J., Kourentzes, N., & Petropoulos, F.
(2015). Forecasting with Temporal Hierarchies ( Department of Econometrics and Business Statistics Working Paper Series 16/15).Bergmeir, C., Hyndman, R. J., & Koo, B.
(2015). A note on the validity of cross-validation for evaluating time series prediction ( Department of Econometrics and Business Statistics Working Paper Series 10/15).Cai, B., Dong, C., & Gao, J.
(2015). Orthogonal Series Estimation in Nonlinear Cointegrating Models with Endogeneity ( Department of Econometrics and Business Statistics Working Paper Series 18/15).Cai, B., Gao, J., & Tjøstheim, D.
(2015). A new class of bivariate threshold cointegration models ( Department of Econometrics and Business Statistics Working Paper Series 01/15).Cheng, T., Gao, J., & Zhang, X.
(2015). Bayesian bandwidth estimation in nonparametric time-varying coefficient models ( Department of Econometrics and Business Statistics Working Paper Series 03/15).Dokumentov, A., & Hyndman, R. J.
(2015). STR: A Seasonal-trend decomposition procedure based on regression ( Department of Econometrics and Business Statistics Working Paper Series 13/15).Dong, C., Gao, J., & Peng, B.
(2015). Partially linear panel data models with cross-sectional dependence and nonstationarity ( Department of Econometrics and Business Statistics Working Paper Series 07/15).Dumrongrittikul, T., & Anderson, H. M.
(2015). How do shocks to domestic factors affect real exchange rates of Asian developing countries ( Department of Econometrics and Business Statistics Working Paper Series 04/15).Feng,G., Gao, J., Peng, B., & Zhang, X
(2015). A varying-coefficient panel data model with theory and an application to U.S. commercial fixed effects: Banks ( Department of Econometrics and Business Statistics Working Paper Series 09/15).Forchini, G., Jiang, B., & Peng, Bin.
(2015). Consistent Estimation in Large Heterogeneous Panels with Multifactor Structure Endogeneity ( Department of Econometrics and Business Statistics Working Paper Series 14/15).Forchini, G., Jiang, B., & Peng, B
(2015). Common shocks in panels with endogenous regressors ( Department of Econometrics and Business Statistics Working Paper Series 08/15).Frazier, D. T., Martin, G. M., & Robert, C. P.
(2015). On Consistency of Approximate Bayesian Computation ( Department of Econometrics and Business Statistics Working Paper Series 19/15).Gao, J.,Peng, B., Ren, Z., & Zhang, X.
(2015). Variable Selection for a Categorical Varying- Coefficient Model with Identifications for Determinants of Body Mass Index. ( Department of Econometrics and Business Statistics Working Paper Series 21/15).Gong, X., & Gao, J.
(2015). Non-parametric kernel estimation of the impact of tax policy on the demand for private health insurance in Australia ( Department of Econometrics and Business Statistics Working Paper Series 06/15).King, M. L., & Sriananthakumar, S.
(2015). Point optimal testing: A survey of the post 1987 literature ( Department of Econometrics and Business Statistics Working Paper Series 05/15).Osman, A. F., & King, M. L.
(2015). A new approach to forecasting based on exponential smoothing with independent regressors. ( Department of Econometrics and Business Statistics Working Paper Series 02/15).Pan, G., Gao, J., Yang, Y., & Guo, M.
(2015). Cross-sectional Independence Test for a Class of Parametric Panel Data Models ( Department of Econometrics and Business Statistics Working Paper Series 17/15).Snyder, R. D., Ord, J. K., Koehler, A. B., McLaren, K. R., & Beaumont, A.
(2015). Forecasting compositional time series: A state space approach ( Department of Econometrics and Business Statistics Working Paper Series 11/15).Taieb, S. B., Huser, R., Hyndman, R.J. & Genton, M. G.
(2015). Probabilistic time series forecasting with boosted additive models: An application to smart meter data ( Department of Econometrics and Business Statistics Working Paper Series 12/15).Wickramasuriya, S.L., Athanasopoulos, G., Hyndman, R.J.
(2015). Forecasting hierarchical and grouped time series through trace minimization ( Department of Econometrics and Business Statistics Working Paper Series 15/15).Zhu, H., Sarafidis, V., Silvapulle, M., & Gao, J.
(2015). Testing for a Structural Break in Dynamic Panel Data Models with Common Factors ( Department of Econometrics and Business Statistics Working Paper Series 20/15).2014
Working Papers
Athanasopoulos, G., Poskitt, D.S., Vahid, F., & Yao, W.
(2014). Determination of long-run and short-run dynamics in EC-VARMA models via canonical correlations ( Department of Econometrics and Business Statistics Working Paper Series 22/14).Atukorala, R., King, M. L., & Sriananthakumar, S.
(2014). Applications of information measures to assess convergence in the central limit theorem ( Department of Econometrics and Business Statistics Working Paper Series 29/14).Bergmeir, C., Hyndman, R. J., & Benítez, J. M.
(2014). Bagging exponential smoothing methods using STL decomposition and box-cox transformation ( Department of Econometrics and Business Statistics Working Paper Series 11/14).Chen, H., & Zhang, X.
(2014). Bayesian estimation for partially linear models with an application to household gasoline consumption ( Department of Econometrics and Business Statistics Working Paper Series 28/14).Chen, J., & Gao, J.
(2014). Semiparametric model selection in panel data models with deterministic trends and cross-sectional dependence ( Department of Econometrics and Business Statistics Working Paper Series 15/14).Cheng, T., Gao, J., & Zhang, X.
(2014). Semiparametric localized bandwidth selection for kernel density estimation ( Department of Econometrics and Business Statistics Working Paper Series 27/14).Cheng, T., Gao, J., & Zhang, X.
(2014). Semiparametric localized bandwidth selection in kernel density estimation ( Department of Econometrics and Business Statistics Working Paper Series 14/14).Dokumentov, A., & Hyndman, R. J.
(2014). Low-dimensional decomposition,smoothing and forecasting of sparsefunctional data ( Department of Econometrics and Business Statistics Working Paper Series 16/14).Dong, C., & Gao, J.
(2014). Specification testing in structural nonparametric cointegration ( Department of Econometrics and Business Statistics Working Paper Series 02/14).Dong, C., Gao, J., & Tjøstheim, D.
(2014). Estimation for single-index and partially linear single-index nonstationary time series models ( Department of Econometrics and Business Statistics Working Paper Series 07/14).Dong, C., Gao, J., Tjøstheim, D., & Yin, J.
(2014). Specification testing for nonlinear multivariate cointegrating regressions ( Department of Econometrics and Business Statistics Working Paper Series 08/14).Dumrongrittikul, T., Anderson, H., & Vahid, F.
(2014). The effects of productivity gains in Asian emerging economies: A global perspective ( Department of Econometrics and Business Statistics Working Paper Series 23/14).Gao, J., & Hong, H.
(2014). Computational implementation of GMM ( Department of Econometrics and Business Statistics Working Paper Series 24/14).Gao, J., & Hong, H.
(2014). Nonparametric regression approach to Bayesian estimation ( Department of Econometrics and Business Statistics Working Paper Series 25/14).Gao, J., Han, X., Pan, G., & Yang, Y.
(2014). High dimensional correlation matrices: CLT and its applications ( Department of Econometrics and Business Statistics Working Paper Series 26/14).Grose, S. D., Martin, G. M., & Poskitt, D.S.
(2014). Bias correction of persistence measures in fractionally integrated models ( Department of Econometrics and Business Statistics Working Paper Series 19/14).Hyndman, R. J., Lee, A., &
Wang, E. (2014). Fast computation of reconciled forecasts for hierarchical and grouped time series ( Department of Econometrics and Business Statistics Working Paper Series 17/14).Khan, M. A. R., & Poskitt, D.S.
(2014). On the theory and practice of singular spectrum analysis forecasting ( Department of Econometrics and Business Statistics Working Paper Series 03/14).Kim, H. Y., McLaren, K. R., & Wong, K. K. W.
(2014). Consumer demand, consumption, and asset pricing: An integrated analysis ( Department of Econometrics and Business Statistics Working Paper Series 04/14).Maneesoonthorn, W., Forbes, C. S., & Martin, G. M.
(2014). Inference on Self-Exciting Jumps in Prices and Volatility using High Frequency Measures ( Department of Econometrics and Business Statistics Working Paper Series 30/14).
Martin, G. M., McCabe, B. P. M., Maneesoonthorn, W., & Robert, C. P. (2014). Approximate bayesian computation in state space models ( Department of Econometrics and Business Statistics Working Paper Series 20/14).
McLaren, K. R., & Yang, O.
(2014). A class of demand systems satisfying global regularity and having complete rank flexibility ( Department of Econometrics and Business Statistics Working Paper Series 06/14).Nadarajah, K., Martin, G. M., & Poskitt, D.S.
(2014). Issues in the estimation of mis-specified models of fractionally integrated processes ( Department of Econometrics and Business Statistics Working Paper Series 18/14).Peng, B., Dong, C., & Gao, J.
(2014). Semiparametric single-index panel data models with cross-sectional dependence ( Department of Econometrics and Business Statistics Working Paper Series 09/14).Polak, J., King, M. L., & Zhang, X.
(2014). A model validation procedure ( Department of Econometrics and Business Statistics Working Paper Series 21/14).Poskitt, D.S., Martin, G. M., & Grose, S. D.
(2014). Bias reduction of long memory parameter estimators via the pre-filtered sieve bootstrap ( Department of Econometrics and Business Statistics Working Paper Series 10/14).Saart, P. W., Gao, J., & Kim, N. H.
(2014). Econometric time series specification testing in a class of multiplicative error models ( Department of Econometrics and Business Statistics Working Paper Series 01/14).Srivastava, P., McLaren, K. R., Wohlgenant, M., & Zhao, X.
(2014). Econometric modelling of price response by alcohol types to inform alcohol tax policies ( Department of Econometrics and Business Statistics Working Paper Series 05/14).Steponavice, I., Hyndman, R., Smith-Miles, K., & Villanova, L.
(2014). Efficient identification of the Pareto optimal set ( Department of Econometrics and Business Statistics Working Paper Series 12/14).Taieb, S. B., & Hyndman, R. J.
(2014). Boosting multi-step autoregressive forecasts ( Department of Econometrics and Business Statistics Working Paper Series 13/14).2013
Working Papers
Anderson, H. M., & Vahid, F.
(2013). Common non-linearities in multiple series of stock market volatility ( Department of Econometrics and Business Statistics Working Paper Series 01/13).Athanasopoulos, G., Deng, M., Li, G., & Song, H.
(2013). Domestic and outbound tourism demand in Australia: A system-of-equations approach ( Department of Econometrics and Business Statistics Working Paper Series 06/13).Cai, B., & Gao, J.
(2013). Hermite series estimation in nonlinear cointegrating models ( Department of Econometrics and Business Statistics Working Paper Series 17/13).Chen, J., Li, D., & Gao, J.
(2013). Non- and semi-parametric panel data models: A selective review ( Department of Econometrics and Business Statistics Working Paper Series 18/13).
Chen, X. B., Silvapulle, P., & Silvapulle, M. (2013). A semiparametric approach to value-at-risk, expected shortfall and optimum asset allocation in stock-bond portfolios ( Department of Econometrics and Business Statistics Working Paper Series 14/13).
Chen, X. B., Gao, J., Li, D., & Silvapulle, P.
(2013). Nonparametric estimation and parametric calibration of time-varying coefficient realized volatility models ( Department of Econometrics and Business Statistics Working Paper Series 21/13).Cheng, T., Gao, J., & Zhang, X.
(2013). Bayesian bandwidth selection in nonparametric time-varying coefficient models ( Department of Econometrics and Business Statistics Working Paper Series 07/13).Dokumentov, A., & Hyndman, R. J.
(2013). Two-dimensional smoothing of mortality rates ( Department of Econometrics and Business Statistics Working Paper Series 26/13).Dong, C., & Gao, J.
(2013). Orthogonal expansion of levy process functionals: Theory and practice ( Department of Econometrics and Business Statistics Working Paper Series 03/13).Dumrongrittikul, T., & Anderson, H. M.
(2013). Do policy-related shocks affect real exchange rates of Asian developing countries%3F ( Department of Econometrics and Business Statistics Working Paper Series 12/13).Gao, J. & Phillips, C.B.
(2013). Functional Coeff icient Nonstationary Regression with Non - and Semi Parametric Cointegration ( Department of Econometrics and Business Statistics Working Paper Series 16/13).Gao, J. & Robinson, P.M.
(2013). Inference on Nonstationary Time Series with Moving Mean ( Department of Econometrics and Business Statistics Working Paper Series 15/13).
Gao, J., & Phillips, P. C. B. (2013). Functional coefficient nonstationary regression with non- and semi-parametric cointegration ( Department of Econometrics and Business Statistics Working Paper Series).
Gao, J., & Robinson, P. M.
(2013). Inference on nonstationary time series with moving mean ( Department of Econometrics and Business Statistics Working Paper Series).Grose, S. D., Martin, G. M., & Poskitt, D. S.
(2013). Bias correction of persistence measures in fractionally integrated models ( Department of Econometrics and Business Statistics Working Paper Series 29/13).Kim, N. H., Saart, P. W., & Gao, J.
(2013). Semi-parametric analysis of shape-invariant engel curves with control function approach ( Department of Econometrics and Business Statistics Working Paper Series 10/13).Koo, B., & Seo, M. H.
(2013). Structural-break models under mis-specification: Implications for forecasting ( Department of Econometrics and Business Statistics Working Paper Series 11/13).Koo, B., & Seo, M. H.
(2013). Structural-break models under mis-specification: Implications for forecasting ( Department of Econometrics and Business Statistics Working Paper Series 08/13).Li, D., Phillips, P. C. B., & Gao, J.
(2013). Uniform consistency of nonstationary kernel-weighted sample covariances for nonparametric regression ( Department of Econometrics and Business Statistics Working Paper Series 27/13).Li, K., Li, D., Zhongwen, L., & Hsiao, C.
(2013). Semiparametric profile likelihood estimation of varying coefficient models with nonstationary regressors ( Department of Econometrics and Business Statistics Working Paper Series 02/13).Maneesoonthorn, W., Forbes, C. S., & Martin, G. M.
(2013). Inference on self-exciting jumps in prices and volatility using high frequency measures ( Department of Econometrics and Business Statistics Working Paper Series 28/13).
Pan, G., Gao, J., & Yang, Y. (2013). Testing independence for a large number of high dimensional random vectors ( Department of Econometrics and Business Statistics Working Paper Series 09/13).
Panagiotelis, A., Smith, M. S.,
& Danaher, P. J. (2013). From Amazon to Apple: Modeling online retail sales, purchase incidence and visit behavior ( Department of Econometrics and Business Statistics Working Paper Series 05/13).Phillips, P. C. B., Li, D., & Gao, J.
(2013). Estimating smooth structural change in cointegration models ( Department of Econometrics and Business Statistics Working Paper Series 22/13).Poskitt, D.S., Grose, S. D., & Martin, G. M.
(2013). Higher-order improvements of the sieve bootstrap for fractionally integrated processes ( Department of Econometrics and Business Statistics Working Paper Series 25/13).Raghavan, M., Athanasopoulos, G., & Silvapulle, P.
(2013). Canadian monetary policy analysis using a structural VARMA model ( Department of Econometrics and Business Statistics Working Paper Series 04/13).Tursunalieva, A., & Silvapulle, P.
(2013). Non-parametric estimation of operational risk and expected shortfall ( Department of Econometrics and Business Statistics Working Paper Series 23/13).Zhang, R., Inder, B. A., & Zhang, X.
(2013). Bayesian estimation of a discrete response model with double rules of sample selection ( Department of Econometrics and Business Statistics Working Paper Series 24/13).Zhang, X., & King, M. L.
(2013). Gaussian kernel GARCH models ( Department of Econometrics and Business Statistics Working Paper Series 19/13).Zhang, X., King, M. L., & Shang, H. L.
(2013). Bayesian bandwidth selection for a nonparametric regession model with mixed types of regressors ( Department of Econometrics and Business Statistics Working Paper Series 13/13).Zhang, X., King, M. L., & Shang, H. L.
(2013). A sampling algorithm for bandwidth estimation in a nonparametric regression model with a flexible error density ( Department of Econometrics and Business Statistics Working Paper Series 20/13).2012
Working Papers
Dong, C., & Gao, J.
(2012). Expansion of lévy process functionals and its application in statistical estimation ( Department of Econometrics and Business Statistics Working Paper Series 02/12).Dong, C., & Gao, J.
(2012). Specification testing driven by orthogonal series in nonstationary time series models ( Department of Econometrics and Business Statistics Working Paper Series 20/12).Dong, C., & Gao, J.
(2012). Solving replication problems in complete market by orthogonal series expansion ( Department of Econometrics and Business Statistics Working Paper Series 07/12).Gao, J., & King, M.
(2012). An improved nonparametric unit root test ( Department of Econometrics and Business Statistics Working Paper Series 16/12).Gao, J.
(2012). Identification, estimation and specification in a class of semiparametic time series models ( Department of Econometrics and Business Statistics Working Paper Series 06/12).Gao, J., Tjøstheim, D., & Yin, J.
(2012). Model specification between parametric and nonparametric cointegration ( Department of Econometrics and Business Statistics Working Paper Series 18/12).Li, D., Tjøstheim, D., & Gao, J.
(2012). Nonlinear regression with Harris recurrent Markov chains ( Department of Econometrics and Business Statistics Working Paper Series 14/12).Li, S., Silvapulle, M. J., Silvapulle, P., & Zhang, X.
(2012). Bayesian approaches to non-parametric estimation of densities on the unit interval ( Department of Econometrics and Business Statistics Working Paper Series 03/12).Li, D., Linton, O., & Lu, Z.
(2012). A flexible semiparametric model for time series ( Department of Econometrics and Business Statistics Working Paper Series 17/12).Olivia, S., & Gibson, J.
(2012). Using engel curves to measure CPI bias for Indonesia ( Department of Econometrics and Business Statistics Working Paper Series 13/12).Pan, G., Gao, J., Yang, Y., & Guo, M.
(2012). Independence test for high dimensional random vectors ( Department of Econometrics and Business Statistics Working Paper Series 01/12).Patrick Saart and Jiti Gao
(2012). Semiparametric methods in nonlinear time series analysis: A selective review ( Department of Econometrics and Business Statistics Working Paper Series 21/12).Poskitt, D. S., Martin, G. M., & Grose, S. D.
(2012). Bias reduction of long memory parameter estimators via the pre-filtered sieve bootstrap ( Department of Econometrics and Business Statistics Working Paper Series 08/12).Poskitt, D.S., & Yao, W.
(2012). VAR modeling and business cycle analysis: A taxonomy of errors ( Department of Econometrics and Business Statistics Working Paper Series 11/12).Poskitt, D.S., Grose, S. D., & Martin, G. M.
(2012). Higher order improvements of the sieve bootstrap for fractionally integrated processes ( Department of Econometrics and Business Statistics Working Paper Series 09/12).Shang, H. L.
(2012). Point and interval forecasts of age-specific fertility rates: A comparison of functional principal component methods ( Department of Econometrics and Business Statistics Working Paper Series 10/12).Snyder, R., Beaumont, A., & Ord, J. K.
(2012). Intermittent demand forecasting for inventory control: A multi-series approach ( Department of Econometrics and Business Statistics Working Paper Series 15/12).Taieb, S. B., & Hyndman, R. J.
(2012). Recursive and direct multi-step forecasting: The best of both worlds ( Department of Econometrics and Business Statistics Working Paper Series 19/12).Weterings, T. A., Harris, M. N., & Hollingsworth, B.
(2012). Extending unobserved heterogeneity – a strategy for accounting for respondent perceptions in the absence of suitable data ( Department of Econometrics and Business Statistics Working Paper Series 12/12).Wright, J., Valenzuela, R., & Chotikapanich, D.
(2012). Measuring poverty and inequality from highly aggregated small area data: The changing fortunes of Latrobe Valley households ( Department of Econometrics and Business Statistics Working Paper Series 04/12).Zhang, R., Inder, B. A., & Zhang, X.
(2012). Parameter estimation for a discrete-response model with double rules of sample selection: A Bayesian approach ( Department of Econometrics and Business Statistics Working Paper Series 05/12).2011
Working Papers
Athanasopoulos, G., & Hyndman, R. J.
(2011). The value of feedback in forecasting competitions ( Department of Econometrics and Business Statistics Working Paper Series 03/11).Breusch, T., & Vahid, F.
(2011). Global temperature trends ( Department of Econometrics and Business Statistics Working Paper Series 04/11).Chen, J., Gao, J., & Li, D.
(2011). Semiparametric trending panel data models with cross-sectional dependence ( Department of Econometrics and Business Statistics Working Paper Series 15/11).Chen, J., Gao, J., & Li, D.
(2011). Estimation in partially linear single-index panel data models with fixed effects ( Department of Econometrics and Business Statistics Working Paper Series 14/11).Chen, J., Gao, J., & Li, D.
(2011). Estimation in single-index panel data models with heterogeneous link functions ( Department of Econometrics and Business Statistics Working Paper Series 12/11).Dong, C., & Gao, J.
(2011). Expansion of Brownian motion functionals and its application in econometric estimation ( Department of Econometrics and Business Statistics Working Paper Series 19/11).Dumrongrittikul, T.
(2011). Real exchange rate movements in developed and developing economies: An interpretation of the Balassa-Samuelsons framework ( Department of Econometrics and Business Statistics Working Paper Series 05/11).Dumrongrittikul, T.
(2011). Do policy-related shocks affect real exchange rates%3F An empirical analysis using sign restrictions and a penalty-function approach ( Department of Econometrics and Business Statistics Working Paper Series 25/11).Gao, J., & King, M.
(2011). A new test in parametric linear models against nonparametric autoregressive errors ( Department of Econometrics and Business Statistics Working Paper Series 20/11).Gao, J., Li, D. & Tjøstheim, D.
(2011). Uniform consistency for nonparametric estimators in null recurrent time series ( Department of Econometrics and Business Statistics Working Paper Series 13/11).Gao, J., Tjøstheim, D., &
Yin, J. (2011). Estimation in threshold autoregressive models with a stationary and a unit root regime ( Department of Econometrics and Business Statistics Working Paper Series 21/11).Gao, J., & Phillips, P. C. B.
(2011). Semiparametric estimation in multivariate nonstationary time series models ( Department of Econometrics and Business Statistics Working Paper Series 17/11).Hyndman, R. J., Booth, H., &
Yasmeen, F. (2011). Coherent mortality forecasting: The product-ratio method with functional time series models ( Department of Econometrics and Business Statistics Working Paper Series 01/11).Khan, M. A. R., & Poskitt, D.S.
(2011). Window length selection and signal-noise separation and reconstruction in singular spectrum analysis ( Department of Econometrics and Business Statistics Working Paper Series 23/11).Khan, M. A. R., & Poskitt, D.S.
(2011). Moment tests for window length selection in singular spectrum analysis of short- and long-memory processes ( Department of Econometrics and Business Statistics Working Paper Series 22/11).King, M. L., Zhang, X., & Akram, M.
(2011). A new procedure for multiple testing of econometric models ( Department of Econometrics and Business Statistics Working Paper Series 07/11).Li, D., Lu, Z., & Linton, O.
(2011). Local linear fitting under near epoch dependence: Uniform consistency with convergence rates ( Department of Econometrics and Business Statistics Working Paper Series 16/11).Liao, Y., & Anderson, H. M.
(2011). Testing for co-jumps in high-frequency financial data: An approach based on first-high-low-last prices ( Department of Econometrics and Business Statistics Working Paper Series 09/11).Ng, J., Forbes, C. S., Martin, G. M., & McCabe, B. P. M.
(2011). Non-parametric estimation of forecast distributions in non-gaussian, non-linear state space models ( Department of Econometrics and Business Statistics Working Paper Series 11/11).Shang, H. L.
(2011). A survey of functional principal component analysis ( Department of Econometrics and Business Statistics Working Paper Series 06/11).Tian, J., & Anderson, H. M.
(2011). Forecasting under structural break uncertainty ( Department of Econometrics and Business Statistics Working Paper Series 08/11).Tregeagle, S., Cox, E., Forbes, C., Humphreys, C., & O'Neill, C.
(2011). Worker time and the cost of stability ( Department of Econometrics and Business Statistics Working Paper Series 02/11).Wongsaart, P., & Gao, J.
(2011). Nonparametric kernel testing in semiparametric autoregressive conditional duration model ( Department of Econometrics and Business Statistics Working Paper Series 18/11).Zhang, X., & King, M. L.
(2011). Bayesian semiparametric GARCH models ( Department of Econometrics and Business Statistics Working Paper Series 24/11).Zhang, X., King, M. L., & Shang, H. L.
(2011). Bayesian estimation of bandwidths for a nonparametric regression model with a flexible error density ( Department of Econometrics and Business Statistics Working Paper Series 10/11).2010
Working Papers
Anderson, H. M., & Vahid, F.
(2010). VARs, cointegration and common cycle restrictions ( Department of Econometrics and Business Statistics Working Paper Series 14/10).Fan, S., & Hyndman, R.
(2010). The price elasticity of electricity demand in South Australia ( Department of Econometrics and Business Statistics Working Paper Series 16/10).Fan, S., & Hyndman, R.
(2010). Short-term load forecasting based on a semi-parametric additive model ( Department of Econometrics and Business Statistics Working Paper Series 17/10).Feng, G., & Serletis, A.
(2010). wp07-10.pdf ( Department of Econometrics and Business Statistics Working Paper Series 07/10).Griffiths, W., Zhang, X., & Zhao, X.
(2010). wp03-10.pdf ( Department of Econometrics and Business Statistics Working Paper Series 3/10).Hauck, K., & Zhao, X.
(2010). wp04-10.pdf ( Department of Econometrics and Business Statistics Working Paper Series 04/10).Hauck, K., & Tsuchiya, A.
(2010). wp06-10.pdf ( Department of Econometrics and Business Statistics Working Paper Series 06/10).Hauck, K., Zhao, X., & Jackson, T.
(2010). wp05-10.pdf ( Department of Econometrics and Business Statistics Working Paper Series 05/10).Hu, S., Poskitt, D.S., & Zhang, X.
(2010). Bayesian adaptive bandwidth kernel density estimation of irregular multivariate distributions ( Department of Econometrics and Business Statistics Working Paper Series 21/10).Khan, M. A. R., & Poskitt, D.S.
(2010). Description length based signal detection in singular spectrum analysis ( Department of Econometrics and Business Statistics Working Paper Series 13/10).Koehler, A. B., Snyder, R. D., Ord, J. K., & Beaumont, A.
(2010). Forecasting compositional time series with exponential smoothing methods ( Department of Econometrics and Business Statistics Working Paper Series 20/10).Liao, Y., Anderson, H. M., & Vahid, F.
(2010). Do jumps matter. Forecasting multivariate realized volatility allowing for common jumps ( Department of Econometrics and Business Statistics Working Paper Series 11/10).Liu, Q., Pitt, D., Zhang, X.
& Wu, X. (2010). A Bayesian approach to parameter estimation for kernel density estimation via transformations ( Department of Econometrics and Business Statistics Working Paper Series 18/10).Livera, A. M. D.
(2010). Automatic forecasting with a modified exponential smoothing state space framework ( Department of Econometrics and Business Statistics Working Paper Series 10/10).Maneesoonthorn, W., Martin, G. M., Forbes, C. S., & Grose, S.
(2010). Probabilistic forecasts of volatility and its risk premia ( Department of Econometrics and Business Statistics Working Paper Series 22/10).McCabe, B. P. M., Martin, G.,
& Freeland, K. (2010). wp02-10.pdf ( Department of Econometrics and Business Statistics Working Paper Series 02/10).Ord, K., Snyder, R., & Beaumont, A.
(2010). Forecasting the intermittent demand for slow-moving items ( Department of Econometrics and Business Statistics Working Paper Series 12/10).Poskitt, D.S., & Sengarapillai, A.
(2010). Dual P-values, evidential tension and balanced tests ( Department of Econometrics and Business Statistics Working Paper Series 15/10).Shang, H. L., Booth, H., & Hyndman, R. J.
(2010). wp08-10.pdf ( Department of Econometrics and Business Statistics Working Paper Series 08/10).Shang, H. L.
(2010). Nonparametric modeling and forecasting electricity demand: an empirical study ( Department of Econometrics and Business Statistics Working Paper Series 19/10).Srivastava, P., & Zhao, X.
(2010). wp01-10.pdf ( Department of Econometrics and Business Statistics Working Paper Series 01/10).Yasmeen, F., Hyndman, R. J., & Erbas, B.
(2010). wp09-10.pdf ( Department of Econometrics and Business Statistics Working Paper Series 09/10).2009
Working Papers
Athanasopoulos, G., de C. Guillén, O. T., Issler, J. V., & Vahid, F.
(2009). Model selection, estimation and forecasting in VAR models with short-run and long-run restrictions ( Department of Econometrics and Business Statistics Working Paper Series 02/09).De Livera, A. M., & Hyndman, R. J.
(2009). Forecasting time series with complex seasonal patterns using exponential smoothing ( Department of Econometrics and Business Statistics Working Paper Series 15/09).de Silva, A., & Athanasopoulos, G.
(2009). Multivariate exponential smoothing for forecasting tourist arrivals to Australia and New Zealand ( Department of Econometrics and Business Statistics Working Paper Series 11/09).Deng, M., & Athanasopoulos, G.
(2009). Modelling Australian domestic and international inbound travel: A spatial-temporal approach ( Department of Econometrics and Business Statistics Working Paper Series 10/09).Feng, G. & Serletis, A.
(2009). Efficiency, technical change, and returns to scale in large U.S. banks: Panel data evidence from an output distance function satisfying theoretical regularity ( Department of Econometrics and Business Statistics Working Paper Series 05/09).Galagedera, D. U. A.
(2009). An analytical derivation of the relation between idiosyncratic volatility and expected stock return ( Department of Econometrics and Business Statistics Working Paper Series 14/09).McCabe, B. P.M., Martin, G. M.,
& Harris, D. (2009). Optimal probabilistic forecasts for counts ( Department of Econometrics and Business Statistics Working Paper Series 07/09).McLaren, K. R., & Zhao, X.
(2009). The econometric specification of input demand systems implied by cost function representations ( Department of Econometrics and Business Statistics Working Paper Series 03/09).McLaren, K. R.
(2009). A new example of a closed form mean-variance representation ( Department of Econometrics and Business Statistics Working Paper Series 01/09).Poskitt, D. S. & Sengarapillai, A.
(2009). Description length and dimensionality reduction in functional data analysis ( Department of Econometrics and Business Statistics Working Paper Series 13/09).Poskitt, D.S.
(2009). Vector autoregresive moving average identification for macroeconomic modeling: Algorithms and theory ( Department of Econometrics and Business Statistics Working Paper Series 12/09).Raghavan, M., Athanasopoulos, G., & Silvapulle, P.
(2009). VARMA models for Malaysian monetary policy analysis ( Department of Econometrics and Business Statistics Working Paper Series 06/09).Shang, H. L., & Hyndman, R. J.
(2009). Nonparametric time series forecasting with dynamic updating ( Department of Econometrics and Business Statistics Working Paper Series 08/09).Snyder, R. D., & Ord, J. K.
(2009). Exponential smoothing and the akaike information criterion ( Department of Econometrics and Business Statistics Working Paper Series 04/09).Taylor, J. W., & Snyder, R. D.
(2009). Forecasting intraday time series with multiple seasonal cycles using parsimonious seasonal exponential smoothing ( Department of Econometrics and Business Statistics Working Paper Series 09/09).2008
Working Papers
Athanasopoulos, G., Hyndman, R. J., Song, H., & Wu, D. C.
(2008). The tourism forecasting competition ( Department of Econometrics and Business Statistics Working Paper Series 10/08).Hyndman, R. J., & Fan, S.
(2008). Density forecasting for long-term peak electricity demand ( Department of Econometrics and Business Statistics Working Paper Series 06/08).Hyndman, R. J., & Shang, H. L.
(2008). Rainbow plots, bagplots and boxplots for functional data ( Department of Econometrics and Business Statistics Working Paper Series 09/08).Iqbal, J., Brooks, R., & Galagedera, D. U. A.
(2008). Testing conditional asset pricing models: An emerging market perspective ( Department of Econometrics and Business Statistics Working Paper Series 03/08).Iqbal, J., Brooks, R., & Galagedera, D. U. A.
(2008). Multivariate tests of asset pricing: Simulation evidence from an emerging market ( Department of Econometrics and Business Statistics Working Paper Series 02/08).Kim, J. H., Song, H., Wong, K., Athanasopoulos, G., & Liu, S.
(2008). Beyond point forecasting: Evaluation of alternative prediction intervals for tourist arrivals ( Department of Econometrics and Business Statistics Working Paper Series 11/08).McLaren, K. R., & Wong, K. K. G.
(2008). The benefit function approach to modeling price-dependent demand systems: An application of duality theory ( Department of Econometrics and Business Statistics Working Paper Series 08/08).Ord, J. K., Hyndman, R. J., Koehler, A. B., & Snyder, R. D.
(2008). Monitoring processes with changing variances ( Department of Econometrics and Business Statistics Working Paper Series 04/08).Ranasinghe, K., & Silvapulle, M. J.
(2008). Semiparametric estimation of duration models when the parameters are subject to inequality constraints and the error distribution is unknown ( Department of Econometrics and Business Statistics Working Paper Series 05/08).Ranasinghe, K., & Silvapulle, M. J.
(2008). Semiparametric estimation of duration models when the parameters are subject to inequality constraints and the error distribution is unknown ( Department of Econometrics and Business Statistics Working Paper Series 01/08).Snyder, R. D., & Koehler, A. B.
(2008). A view of damped trend as incorporating a tracking signal into a state space model ( Department of Econometrics and Business Statistics Working Paper Series 07/08).2007
Working Papers
Akram, M., Hyndman, R. J., & Ord, J. K.
(2007). Non-linear exponential smoothing and positive data ( Department of Econometrics and Business Statistics Working Paper Series 14/07).Athanasopoulos, G., Ahmed, R. A., & Hyndman, R. J.
(2007). Hierarchical forecasts for Australian domestic tourism ( Department of Econometrics and Business Statistics Working Paper Series 12/07).Athanasopoulos, G., Poskitt, D.S., & Vahid, F.
(2007). Two canonical VARMA forms: Scalar component models vis-à-vis the Echelon form ( Department of Econometrics and Business Statistics Working Paper Series 10/07).Bialowas, A., Farrell, L., Harris, M. N., & Polidano, C.
(2007). Long-run effects of BSE on meat consumption ( Department of Econometrics and Business Statistics Working Paper Series 13/07).de Silva, A., Hyndman, R. J., & Snyder, R. D.
(2007). The vector innovation structural time series framework: a simple approach to multivariate forecasting ( Department of Econometrics and Business Statistics Working Paper Series 03/07).Hyndman, R. J., & Khandakar, Y.
(2007). Automatic time series forecasting: The forecast package for R ( Department of Econometrics and Business Statistics Working Paper Series 06/07).Hyndman, Rob J., Ahmed, R. A., & Athanasopoulos, G.
(2007). Optimal combination forecasts for hierarchical time series ( Department of Econometrics and Business Statistics Working Paper Series 09/07).Kim, G., Silvapulle, M. J., & Silvapulle, P.
(2007). Estimating the error distribution in the multivariate heteroscedastic time series models ( Department of Econometrics and Business Statistics Working Paper Series 08/07).Kim, G., Silvapulle, M. J., & Silvapulle, P.
(2007). Semiparametric estimation of the dependence parameter of the error terms in multivariate regression ( Department of Econometrics and Business Statistics Working Paper Series 01/07).Martin, G. M., Reidy, A., & Wright, J.
(2007). Does the option market produce superior forecasts of noise-corrected volatility measures%3F ( Department of Econometrics and Business Statistics Working Paper Series 05/07).McLaren, K. R., & Wong, K. K. G.
(2007). Effective global regularity and empirical modeling of direct, inverse and mixed demand systems ( Department of Econometrics and Business Statistics Working Paper Series 02/07).Ouwehand, P., Hyndman, R. J.,
de Kok, T. G., & van Donselaar, K. H. (2007). A state space model for exponential smoothing with group seasonality ( Department of Econometrics and Business Statistics Working Paper Series 07/07).Snyder, R. D., & Beaumont, A.
(2007). A comparison of methods for forecasting demand for slow moving car parts ( Department of Econometrics and Business Statistics Working Paper Series 15/07).Snyder, R. D., Martin, G. M., Gould, P., & Feigin, P. D.
(2007). An assessment of alternative state space models for count time series ( Department of Econometrics and Business Statistics Working Paper Series 04/07).Zhang, X., Brooks, R. D., & King, M. L.
(2007). A Bayesian approach to bandwidth selection for multivariate kernel regression with an application to state-price density estimation ( Department of Econometrics and Business Statistics Working Paper Series 11/07).2006
Working Papers
Athanasopoulos, G., & Hyndman, R. J.
(2006). Modelling and forecasting Australian domestic tourism ( Department of Econometrics and Business Statistics Working Paper Series 19/06).Athanasopoulos, G., & Vahid, F.
(2006). A complete VARMA modelling methodology based on scalar components ( Department of Econometrics and Business Statistics Working Paper Series 02/06).Athanasopoulos, G., & Vahid, F.
(2006). VARMA versus VAR for macroeconomic forecasting ( Department of Econometrics and Business Statistics Working Paper Series 04/06).Booth, H., Hyndman, R. J., Tickle, L., & de Jong, P.
(2006). Lee-Carter mortality forecasting: A multi-country comparison of variants and extensions ( Department of Econometrics and Business Statistics Working Paper Series 13/06).Cornwell, K.
(2006). Language and labour in South Africa: A new approach for a new South Africa ( Department of Econometrics and Business Statistics Working Paper Series 05/06).Deng, M.
(2006). An anisotropic model for spatial processes ( Department of Econometrics and Business Statistics Working Paper Series 07/06).Forbes, C., Inder, B., & Raman, S.
(2006). Measuring the cost of leaving care in Victoria ( Department of Econometrics and Business Statistics Working Paper Series 18/06).Forchini, G.
(2006). Tests for over-identifying restrictions in partially identified linear structural equations ( Department of Econometrics and Business Statistics Working Paper Series 20/06).Forchini, G.
(2006). The asymptotic distribution of the LIML estimator in a partially identified structural equation ( Department of Econometrics and Business Statistics Working Paper Series 01/06).
Gael M. Martin, Andrew Reidy and Jill Wright (2006). Assessing the impact of market microstructure noise and random jumps on the relative forecasting performance of option-implied and returns-based volatility ( Department of Econometrics and Business Statistics Working Paper Series 10/06).
Grose, S. D., & Poskitt, D. S.
(2006). The finite-sample properties of autoregressive approximations of fractionally-integrated and non-invertible processes ( Department of Econometrics and Business Statistics Working Paper Series 15/06).Gunatilaka, R., Chotikapanich, D., & Inder, B.
(2006). Impact of structural change in education, industry and infrastructure on income distribution in Sri Lanka ( Department of Econometrics and Business Statistics Working Paper Series 21/06).Gunatilaka,R. & Chotikapanich, D.
(2006). Inequality trends and determinants in Sri Lanka 1980-2002: A shapley approach to decomposition ( Department of Econometrics and Business Statistics Working Paper Series 06/06 Inequality Trends and Determinants in Sri Lanka 1980/2002).Hyndman, R. J., & Akram, M.
(2006). Some nonlinear exponential smoothing models are unstable ( Department of Econometrics and Business Statistics Working Paper Series 03/06).Hyndman, R. J., & Booth, H.
(2006). Stochastic population forecasts using functional data models for mortality, fertility and migration ( Department of Econometrics and Business Statistics Working Paper Series 14/06).Kim, J., Silvapulle, P., & Hyndman, R. J.
(2006). Half-life estimation based on the bias-corrected bootstrap: A highest density region approach ( Department of Econometrics and Business Statistics Working Paper Series 11/06).Low, C. N., Anderson, H., & Snyder, R. D.
(2006). Beveridge-Nelson decomposition with Markov switching ( Department of Econometrics and Business Statistics Working Paper Series 17/06).Poskitt, D. S.
(2006). Properties of the sieve bootstrap for fractionally integrated and non-invertible processes ( Department of Econometrics and Business Statistics Working Paper Series 12/06).Silvapulle, P., & Zhang, X.
(2006). Assessing dependence changes in the Asian financial market returns using plots based on nonparametric measures ( Department of Econometrics and Business Statistics Working Paper Series 09/06).Snyder, R. D., & Koehler, A. B.
(2006). Incorporating a tracking signal into state space models for exponential smoothing ( Department of Econometrics and Business Statistics Working Paper Series 16/06).Strickland, C. M., Martin, G., & Forbes, C. S.
(2006). Parameterisation and efficient MCMC estimation of non-gaussian state space models ( Department of Econometrics and Business Statistics Working Paper Series 22/06).Ye, A., Hyndman, R. J., & Li, Z.
(2006). Local linear multivariate regression with variable bandwidth in the presence of heteroscedasticity ( Department of Econometrics and Business Statistics Working Paper Series 08/06).2005
Working Papers
Armstrong, J. S., & Green, K. C.
(2005). Demand forecasting: Evidence-based methods ( Department of Econometrics and Business Statistics Working Paper Series 24/05).Bhowmik, J. L., & King, M. L.
(2005). Parameter estimation in semi-linear models using a maximal invariant likelihood function ( Department of Econometrics and Business Statistics Working Paper Series 18/05).Bhowmik, J. L., & King, M. L.
(2005). Deriving tests of the semi-linear regression model using the density function of a maximal invariant ( Department of Econometrics and Business Statistics Working Paper Series 19/05).Billah, B., King, M. L., Snyder, R. D., & Koehler, A. B.
(2005). Exponential smoothing model selection for forecasting ( Department of Econometrics and Business Statistics Working Paper Series 06/05).Bissoondoyal-Bheenick, E., Brooks, R.,
& Yip, A. Y.N. (2005). Determinants of sovereign ratings: A comparison of case-based reasoning and ordered probit approaches ( Department of Econometrics and Business Statistics Working Paper Series 09/05).Brooks, R., & Harris, E.
(2005). An analysis of Watermove water markets ( Department of Econometrics and Business Statistics Working Paper Series 10/05).de Gooijer, J. G., & Hyndman, R. J.
(2005). 25 years of IIF time series forecasting: A selective review ( Department of Econometrics and Business Statistics Working Paper Series 12/05 25).Erbas, B., Hyndman, R. J.,
& Gertig, D. M. (2005). Forecasting age-specific breast cancer mortality using functional data models ( Department of Econometrics and Business Statistics Working Paper Series 03/05).Forchini, G.
(2005). Some properties of tests for possibly unidentified parameters ( Department of Econometrics and Business Statistics Working Paper Series 21/05).Forchini, G.
(2005). On the bimodality of the exact distribution of the TSLS estimator ( Department of Econometrics and Business Statistics Working Paper Series 14/05).Forchini, G.
(2005). Weighted average power similar tests for structural change for the Gaussian linear regression model ( Department of Econometrics and Business Statistics Working Paper Series 20/05).Galagedera, D. U. A., & Brooks, R. D.
(2005). Is systematic downside beta risk really priced%3F Evidence in emerging market data ( Department of Econometrics and Business Statistics Working Paper Series 11/05).Gay, R.
(2005). Minimum variance unbiased maximum likelihood estimation of the extreme value index ( Department of Econometrics and Business Statistics Working Paper Series 08/05).Green, K. C., & Armstrong, J. S.
(2005). Competitor-oriented objectives: The myth of market share ( Department of Econometrics and Business Statistics Working Paper Series 17/05).Guillén, O. T. d. C., Issler, J. V., & Athanasopoulos, G.
(2005). Forecasting accuracy and estimation uncertainty using VAR models with short- and long-term economic restrictions: A Monte-Carlo Study ( Department of Econometrics and Business Statistics Working Paper Series 15/05).Hyndman, R. J., & Koehler, A. B.
(2005). Another look at measures of forecast accuracy ( Department of Econometrics and Business Statistics Working Paper Series 13/05).Hyndman, R. J., & Ullah Shahid, M.
(2005). Robust forecasting of mortality and fertility rates: a functional data approach ( Department of Econometrics and Business Statistics Working Paper Series 02/05).
Jae H. Kim and Hristos Doucouliagos (2005). Realized volatility and correlation in grain futures markets: Testing for spill-over effects ( Department of Econometrics and Business Statistics Working Paper Series 22/05).
Ji, P. I., & Kim, J. H.
(2005). Real interest rate linkages in the Pacific Basin region ( Department of Econometrics and Business Statistics Working Paper Series 23/05).Meyer, D., & Hyndman, R. J.
(2005). Rating forecasts for television programs ( Department of Econometrics and Business Statistics Working Paper Series 01/05).Ord, J. K., Snyder, R. D., Koehler, A. B., Hyndman, R. J., & Leeds, M.
(2005). Time series forecasting: The case for the single source of error state space ( Department of Econometrics and Business Statistics Working Paper Series 07/05).Poskitt, D. S.
(2005). Autoregressive approximation in nonstandard situations: The non-invertible and fractionally integrated cases ( Department of Econometrics and Business Statistics Working Paper Series 16/05).Poskitt, D. S., & Skeels, C. L.
(2005). Small concentration asymptotics and instrumental variables inference ( Department of Econometrics and Business Statistics Working Paper Series 04/05).Snyder, R. D.
(2005). A pedant's approach to exponential smoothing ( Department of Econometrics and Business Statistics Working Paper Series 05/05).2004
Working Papers
Anderson, H. M., & Low, C. N.
(2004). Random walk smooth transition autoregressive models ( Department of Econometrics and Business Statistics Working Paper Series 22/04).Anderson, H. M., Low, C., N., & Snyder, R.
(2004). Single source of error state space approach to the Beveridge Nelson decomposition ( Department of Econometrics and Business Statistics Working Paper Series 21/04).Cornwell, K., & Inder, B.
(2004). Migration and unemployment in South Africa: When motivation surpasses the theory ( Department of Econometrics and Business Statistics Working Paper Series 02/04).Dark, J.
(2004). Basis convergence and long memory in volatility when dynamic hedging with SPI futures ( Department of Econometrics and Business Statistics Working Paper Series 06/04).Dark, J.
(2004). Long term hedging of the Australian All Ordinaries Index using a bivariate error correction FIGARCH model ( Department of Econometrics and Business Statistics Working Paper Series 07/04).Dark, J.
(2004). Bivariate error correction FIGARCH and FIAPARCH models on the Australian All Ordinaries Index and its SPI futures ( Department of Econometrics and Business Statistics Working Paper Series 04/04).Dark, J.
(2004). Long memory in the volatility of the Australian All Ordinaries Index and the Share Price Index futures ( Department of Econometrics and Business Statistics Working Paper Series 05/04).Galagedera, D. U. A., & Maharaj, E. A.
(2004). Wavelet timescales and conditional relationship between higher-order systematic co-moments and portfolio returns: Evidence in Australian data ( Department of Econometrics and Business Statistics Working Paper Series 16/04).Galagedera, D. U. A. & Faff, R.
(2004). Modelling the risk and return relation conditional on market volatility and market conditions ( Department of Econometrics and Business Statistics Working Paper Series 08/04).Gay, R.
(2004). Adaptive premiums for evolutionary claims in non-life insurance ( Department of Econometrics and Business Statistics Working Paper Series 25/04).Gay, R.
(2004). The power principle and tail-fatness uncertainty ( Department of Econometrics and Business Statistics Working Paper Series 01/04).Gillman, M., & Harris, M. N.
(2004). Inflation, financial development and endogenous growth ( Department of Econometrics and Business Statistics Working Paper Series 24/04).Gillman, M., & Harris, M. N.
(2004). Inflation, financial development and growth in transition countries ( Department of Econometrics and Business Statistics Working Paper Series 23/04).Gould, P., Koehler, A. B., Vahid-Araghi, F., Snyder, R. D., Ord, J. K., & Hyndman, R. J.
(2004). Forecasting time-series with multiple seasonal patterns ( Department of Econometrics and Business Statistics Working Paper Series 28/04).Green, K. C., & Armstrong, J. S.
(2004). Structured analogies for forecasting ( Department of Econometrics and Business Statistics Working Paper Series 17/04).Green, K. C.
(2004). Further evidence on game theory, simulated interaction, and unaided judgement for forecasting decisions in conflicts ( Department of Econometrics and Business Statistics Working Paper Series 18/04).Green, K. C., & Armstrong, J. S.
(2004). Value of expertise for forecasting decisions in conflicts ( Department of Econometrics and Business Statistics Working Paper Series 27/04).Harris, M. N., & Zhao, X.
(2004). Modelling tobacco consumption with a zero-inflated ordered probit model ( Department of Econometrics and Business Statistics Working Paper Series 14/04).Inder, B.
(2004). Economic growth and contraction and their impact on the poor ( Department of Econometrics and Business Statistics Working Paper Series 03/04).McCabe, B. P. M., Martin, G. M., & Freeland, R. K.
(2004). Testing for dependence in non-Gaussian time series data ( Department of Econometrics and Business Statistics Working Paper Series 13/04).Poskitt, D. S. & Skeels, C. L.
(2004). Assessing the magnitude of the concentration parameter in a simultaneous equations model ( Department of Econometrics and Business Statistics Working Paper Series 29/04).Poskitt, D. S., & Zhang, J.
(2004). Estimating components in finite mixtures and hidden Markov models ( Department of Econometrics and Business Statistics Working Paper Series 10/04).Poskitt, D. S.
(2004). On the identification and estimation of partially nonstationary ARMAX systems ( Department of Econometrics and Business Statistics Working Paper Series 20/04).Poskitt, D. S.
(2004). Some results on the identification and estimation of vector ARMAX processes ( Department of Econometrics and Business Statistics Working Paper Series 12/04).Poskitt, D. S. & Skeels, C. L.
(2004). Approximating the distribution of the instrumental variables estimator when the concentration parameter is small ( Department of Econometrics and Business Statistics Working Paper Series 19/04).Sanford, A. D., & Martin, G.
(2004). Bayesian analysis of continuous time models of the Australian short rate ( Department of Econometrics and Business Statistics Working Paper Series 11/04).Snyder, R. D.
(2004). Exponential smoothing: A prediction error decomposition principle ( Department of Econometrics and Business Statistics Working Paper Series 15/04).Zhang, X., & King, M. L.
(2004). Box-Cox stochastic volatility models with heavy-tails and correlated errors ( Department of Econometrics and Business Statistics Working Paper Series 26/04).Zhang, X., King, M. L., & Hyndman, R. J.
(2004). Bandwidth selection for multivariate kernel density estimation using MCMC ( Department of Econometrics and Business Statistics Working Paper Series 09/04).2003
Working Papers
Anderson, H. M., & Vahid, F.
(2003). Nonlinear correlograms and partial autocorrelograms ( Department of Econometrics and Business Statistics Working Paper Series 19/03).Anderson, H. M., & Vahid, F.
(2003). The decline in income growth volatility in the United States: Evidence from regional data ( Department of Econometrics and Business Statistics Working Paper Series 21/03).Billah, M. B., Hyndman, R. J., & Koehler, A. B.
(2003). Empirical information criteria for time series forecasting model selection ( Department of Econometrics and Business Statistics Working Paper Series 02/03).Brown, S., Farrell, L., & Harris, M. N.
(2003). Who are the self-employed%3F A new approach ( Department of Econometrics and Business Statistics Working Paper Series 11/03).Campbell, R., Forbes, C. S., Koedijk, K., & Kofman, P.
(2003). Diversification meltdown or the impact of fat tails on conditional correlation%3F ( Department of Econometrics and Business Statistics Working Paper Series 18/03).Chotikapanich, D., & Griffiths, W. E.
(2003). Averaging Lorenz curves ( Department of Econometrics and Business Statistics Working Paper Series 22/03).Flynn, D. B., Grose, S. D., Martin, G. M., & Martin, V. L.
(2003). Pricing Australian S%26P200 options: A Bayesian approach based on generalized distributional forms ( Department of Econometrics and Business Statistics Working Paper Series 06/03).Forbes, C. S., Martin, G. M., & Wright, J.
(2003). Bayesian estimation of a stochastic volatility model using option and spot prices: Application of a bivariate Kalman filter ( Department of Econometrics and Business Statistics Working Paper Series 17/03).Galagedera, D. U. A., & Shami, R.
(2003). Association between Markov regime-switching market volatility and beta risk: Evidence from Dow Jones industrial securities ( Department of Econometrics and Business Statistics Working Paper Series 20/03).Gay, R.
(2003). General insurance premiums when tail fatness is unknown: A fat premium representation theorem ( Department of Econometrics and Business Statistics Working Paper Series 13/03).Hall, P. G., Hyndman, R. J., & Fan, Y.
(2003). Non parametric confidence intervals for receiver operating characteristic curves ( Department of Econometrics and Business Statistics Working Paper Series 12/03).Hyndman, R. J., Akram, M., & Archibald, B.
(2003). Invertibility conditions for exponential smoothing models ( Department of Econometrics and Business Statistics Working Paper Series 03/03).Maharaj, E. A.
(2003). Using evolutionary spectra to forecast time series ( Department of Econometrics and Business Statistics Working Paper Series 04/03).Martin, G. M., Forbes, C. S., & Martin, V. L.
(2003). Implicit Bayesian inference using option prices ( Department of Econometrics and Business Statistics Working Paper Series 05/03).McCabe, B. P. M., & Martin, G. M.
(2003). Coherent predictions of low count time series ( Department of Econometrics and Business Statistics Working Paper Series 08/03).McCabe, B .P. M., Martin, G. M., & Tremayne, A. R.
(2003). Persistence and nonstationary models ( Department of Econometrics and Business Statistics Working Paper Series 16/03).Sanford, A. D., & Martin, G. M.
(2003). Simulation-based Bayesian estimation of affine term structure models ( Department of Econometrics and Business Statistics Working Paper Series 15/03).Shenstone, L., & Hyndman, R. J.
(2003). Stochastic models underlying Croston's method for intermittent demand forecasting ( Department of Econometrics and Business Statistics Working Paper Series 01/03).Strickland, C. M., Forbes, C. S., & Martin, G. M.
(2003). Bayesian analysis of the stochastic conditional duration model ( Department of Econometrics and Business Statistics Working Paper Series 14/03).Tse, Y. K., & Zhang, X.
(2003). A Monte Carlo investigation of some tests for stochastic dominance ( Department of Econometrics and Business Statistics Working Paper Series 07/03).Woodward, G., & Anderson, H.
(2003). Does beta react to market conditions%3F Estimates of bull and bear betas using a nonlinear market model with an endogenous threshold parameter ( Department of Econometrics and Business Statistics Working Paper Series 09/03).Zhang, X., & King, M. L.
(2003). Estimation of asymmetric Box-Cox stochastic volatility models using MCMC simulation ( Department of Econometrics and Business Statistics Working Paper Series 10/03).2002
Working Papers
Anderson, H. M., Athanasopoulos, G., & Vahid, F.
(2002). Nonlinear autoregresssive leading indicator models of output in G-7 countries ( Department of Econometrics and Business Statistics Working Paper Series 20/02 Nonlinear Autoregresssive Leading Indicator Models of Output in G/7).Anderson, H. M.
(2002). Choosing lag lengths in nonlinear dynamic models ( Department of Econometrics and Business Statistics Working Paper Series 21/02).Athanasopoulos, G., & Vahid, F.
(2002). Statistical inference on changes in income inequality in Australia ( Department of Econometrics and Business Statistics Working Paper Series 09/02).Forbes, C. S., Martin, G. M., & Wright, J.
(2002). Bayesian estimation of a stochastic volatility model using option and spot prices ( Department of Econometrics and Business Statistics Working Paper Series 02/02).Fry, T. R. L., & Harris, M. N.
(2002). The DOGEV model ( Department of Econometrics and Business Statistics Working Paper Series 07/02).Hall, P., & Hyndman, R. J.
(2002). An improved method for bandwidth selection when estimating ROC curves ( Department of Econometrics and Business Statistics Working Paper Series 11/02).Hanlon, B., & Forbes, C.
(2002). Model selection criteria for segmented time series from a Bayesian approach to information compression ( Department of Econometrics and Business Statistics Working Paper Series 08/02).Hibbard, R. E. J., Brown, R., & McLaren, K. R.
(2002). Nonsimultaneity and futures option pricing: Simulation and empirical evidence ( Department of Econometrics and Business Statistics Working Paper Series 13/02).Hyndman, R. J., King, M. L., Pitrun, I., & Billah, B.
(2002). Local linear forecasts using cubic smoothing splines ( Department of Econometrics and Business Statistics Working Paper Series 10/02).Lim, G. C., Martin, G. M., & Martin, V. L.
(2002). Parametric pricing of higher order moments in S%26P500 options ( Department of Econometrics and Business Statistics Working Paper Series 01/02).Lim, G.C., Martin, G.M.,
& Martin, V.L. (2002). Pricing currency options in tranquil markets: Modelling volatility frowns ( Department of Econometrics and Business Statistics Working Paper Series 04/02).Powell, A. A., McLaren, K. R., Pearson, K.R., & Rimmer, M.
(2002). Cobb-Douglas utility - eventually! ( Department of Econometrics and Business Statistics Working Paper Series 12/02).Shami, R. G., & Forbes, C. S.
(2002). Non-linear modelling of the Australian business cycle using a leading indicator ( Department of Econometrics and Business Statistics Working Paper Series 05/02).Snyder, R. D., & Forbes, C. S.
(2002). Reconstructing the Kalman filter for stationary and non stationary time series ( Department of Econometrics and Business Statistics Working Paper Series 14/02).Snyder, R. D., Koehler, A. B., Hyndman, R. J., & Ord, J. K.
(2002). Exponential smoothing for inventory control: Means and variances of lead-time demand ( Department of Econometrics and Business Statistics Working Paper Series 03/02).Tse, Y. K., Zhang, X.,
& Yu, J. (2002). Estimation of hyperbolic diffusion using MCMC method ( Department of Econometrics and Business Statistics Working Paper Series 18/02).Wong, G. K. K., & McLaren, K. R.
(2002). Modelling regular and estimable inverse demand systems: A distance function approach ( Department of Econometrics and Business Statistics Working Paper Series 06/02).Yu, J., Yang, Z., & Zhang, X.
(2002). A class of nonlinear stochastic volatility models and its implications on pricing currency options ( Department of Econometrics and Business Statistics Working Paper Series 17/02).Zhang, X., & King, M. L.
(2002). Influence diagnostics in GARCH processes ( Department of Econometrics and Business Statistics Working Paper Series 19/02).Zhao, X.
(2002). Who bears the burden and who receives the gain%3F - The case of GWRDC R%26D investments in the Australian grape and wine industry ( Department of Econometrics and Business Statistics Working Paper Series 15/02).Zhao, X., Mullen, J. D., Griffith, G. R., Piggott, R. R., & Griffiths, W. E.
(2002). The economic incidence of R%26D and promotion investments in the Australian beef industry ( Department of Econometrics and Business Statistics Working Paper Series 16/02).2001
Working Papers
Anderson, H. M., & Vahid, F.
(2001). Market architecture and nonlinear dynamics of Australian stock and future indices ( Department of Econometrics and Business Statistics Working Paper Series 03/01).Athanasopoulos, G., Anderson, H. M., & Vahid, F.
(2001). Capturing the shape of business cycles with nonlinear autoregressive leading indicator models ( Department of Econometrics and Business Statistics Working Paper Series 07/01).Erbas, B., & Hyndman, R. J.
(2001). Statistical methodological issues in studies of air pollution and respiratory disease ( Department of Econometrics and Business Statistics Working Paper Series 06/01).Hyndman, R. J., & Billah, B.
(2001). Unmasking the Theta method ( Department of Econometrics and Business Statistics Working Paper Series 05/01).Hyndman, R. J., Koehler, A. B., Ord, J. K., & Snyder, R. D.
(2001). Prediction intervals for exponential smoothing state space models ( Department of Econometrics and Business Statistics Working Paper Series 11/01).Issler, J. V., & Vahid, F.
(2001). The missing link: Using the NBER recession indicator to construct coincident and leading indices of economic activity ( Department of Econometrics and Business Statistics Working Paper Series 09/01).Maharaj, E. A.
(2001). Comparison of non-stationary time series in the frequency domain ( Department of Econometrics and Business Statistics Working Paper Series 01/01).McLean, A.
(2001). On the nature and role of hypothesis tests ( Department of Econometrics and Business Statistics Working Paper Series 04/01).Racine, J., & Hyndman, R. J.
(2001). Using R to teach econometrics ( Department of Econometrics and Business Statistics Working Paper Series 10/01).Sarin, R., & Vahid, F.
(2001). Strategy similarity and coordination ( Department of Econometrics and Business Statistics Working Paper Series 08/01).Vahid, F., & Issler, J. V.
(2001). The importance of common cyclical features in VAR analysis: A Monte Carlo study ( Department of Econometrics and Business Statistics Working Paper Series 02/01).2000
Working Papers
Anderson, H. M., & Vahid, F.
(2000). Predicting the probability of a recession with nonlinear autoregressive leading indicator models ( Department of Econometrics and Business Statistics Working Paper Series 03/00).Cai, T., Hyndman, R. J.,
& Wand, M. P. (2000). Mixed model-based hazard estimation ( Department of Econometrics and Business Statistics Working Paper Series 11/00).Chalmers, J., & Kalb, G.
(2000). Are casual jobs a freeway to permanent employment ( Department of Econometrics and Business Statistics Working Paper Series 08/00).Forbes, C. S., & Kofman, P.
(2000). Bayesian soft target zones ( Department of Econometrics and Business Statistics Working Paper Series 04/00).Forbes, C. S., Snyder, R. D., & Shami, R. G.
(2000). Bayesian exponential smoothing ( Department of Econometrics and Business Statistics Working Paper Series 07/00).Grose, S., & Mclaren, K.
(2000). Estimating demand with varied levels of aggregation ( Department of Econometrics and Business Statistics Working Paper Series 01/00).Grose, S., & McLaren, K.
(2000). An EM algorithm for modelling variably-aggregated demand ( Department of Econometrics and Business Statistics Working Paper Series 02/00).Hyndman, R. J., Koehler, A. B.,
Snyder, R. D., & Grose, S. (2000). A state space framework for automatic forecasting using exponential smoothing methods ( Department of Econometrics and Business Statistics Working Paper Series 09/00).Martin, G. M., Forbes, C. S., & Martin, V. L.
(2000). Implicit Bayesian inference using option prices ( Department of Econometrics and Business Statistics Working Paper Series 05/00).Shami, R. G., & Forbes, C. S.
(2000). A structural time series model with Markov switching ( Department of Econometrics and Business Statistics Working Paper Series 10/00).Strachan, R.
(2000). Valid Bayesian estimation of the cointegrating error correction model ( Department of Econometrics and Business Statistics Working Paper Series 06/00).1999
Working Papers
Anderson, H. M., Kwark, N. S., & Vahid, F.
(1999). Does international trade synchronize business cycles%3F ( Department of Econometrics and Business Statistics Working Paper Series 08/99).
Elizabeth Ann Maharaj (1999). A test for the difference parameter of the ARFIMA model using the moving blocks bootstrap ( Department of Econometrics and Business Statistics Working Paper Series 11/99).
Evans, M.
(1999). School-leavers' transition to tertiary study: A literature review ( Department of Econometrics and Business Statistics Working Paper Series 03/99).Fry, J., Fry, T. R. L., & Peter, M. W.
(1999). Inter- regional migration in Australia: An applied economic analysis ( Department of Econometrics and Business Statistics Working Paper Series 05/99).Fry, T. R. L., Broadbent, S., & Dixon, J. M.
(1999). Estimating advertising half- life and the data interval bias ( Department of Econometrics and Business Statistics Working Paper Series 06/99).Hyndman, R. J., & Grunwald, G. K.
(1999). Generalized additive modelling of mixed distribution Markov models with application to Melbourne rainfall ( Department of Econometrics and Business Statistics Working Paper Series 02/99).Koehler, A. B., Snyder, R. D., & Ord, J. K.
(1999). Forecasting models and prediction intervals for the multiplicative Holt- Winters method ( Department of Econometrics and Business Statistics Working Paper Series 01/99).Maharaj, E. A., & Inder, B. A.
(1999). Forecasting time series from clusters ( Department of Econometrics and Business Statistics Working Paper Series 09/99).McLean, A.
(1999). The predictive approach to teaching statistics ( Department of Econometrics and Business Statistics Working Paper Series 04/99).Sarin, R., & Vahid, F.
(1999). Predicting how people play games: A simple dynamic model of choice. ( Department of Econometrics and Business Statistics Working Paper Series 12/99).Snyder, R. D., & Forbes, C. S.
(1999). Understanding the Kalman filter: An object oriented programming perspective ( Department of Econometrics and Business Statistics Working Paper Series 14/99).Snyder, R. D., Koehler, A., & Ord, K.
(1999). Forecasting for inventory control with exponential smoothing ( Department of Econometrics and Business Statistics Working Paper Series 10/99).Snyder, R. D.
(1999). Forecasting sales of slow and fast moving inventories ( Department of Econometrics and Business Statistics Working Paper Series 07/99).Strachan, R. W., & Inder, B.
(1999). Bayesian trace statistics for the reduced rank regression model ( Department of Econometrics and Business Statistics Working Paper Series 13/99).1998
Working Papers
Bashtannyk, D. M., & Hyndman, R. J.
(1998). Bandwidth selection for Kernel conditional density estimation ( Department of Econometrics and Business Statistics Working Paper Series 16/98).Bollen, B., & Inder, B.
(1998). A general volatility framework and the generalised historical volatility estimator ( Department of Econometrics and Business Statistics Working Paper Series 10/98).Evans, M., & Farley, A.
(1998). Institutional characteristics and the relationship between students' first-year university and final-year secondary school academic performance ( Department of Econometrics and Business Statistics Working Paper Series 18/98).Fraccaro, R., Hyndman, R., & Veevers, A.
(1998). Residual diagnostic plots for checking for model mis-specification in time series regression ( Department of Econometrics and Business Statistics Working Paper Series 12/98).Harris, M. N., Macquarie, L. R., & Siouclis, A. J.
(1998). A comparison of alternative estimators for binary panel probit models ( Department of Econometrics and Business Statistics Working Paper Series 04/98).Hossain, M. Z., & King, M. L.
(1998). Model selection when a key parameter is constrained to be an interval ( Department of Econometrics and Business Statistics Working Paper Series 15/98).Hyndman, R. J., & Yao, Q.
(1998). Nonparametric estimation and symmetry tests for conditional density functions ( Department of Econometrics and Business Statistics Working Paper Series 17/98).Laskar, M. R., & King, M. L.
(1998). Comparisons of estimators and tests based on modified likelihood and message length functions ( Department of Econometrics and Business Statistics Working Paper Series 06/98).Laskar, M. R., & King, M. L.
(1998). Modified likelihood and related methods of handling nuisance parameters in the linear regression model ( Department of Econometrics and Business Statistics Working Paper Series 05/98).Martin, G. M.
(1998). U.S. deficit sustainability: A new approach based on multiple endogenous breaks ( Department of Econometrics and Business Statistics Working Paper Series 01/98).Nahar, S., & Inder, B.
(1998). Testing convergence in economic growth for OECD countries ( Department of Econometrics and Business Statistics Working Paper Series 14/98).Shami, R. G., & Snyder, R. D.
(1998). Exponential smoothing methods of forecasting and general ARMA time series representations ( Department of Econometrics and Business Statistics Working Paper Series 03/98).Smith, M., Yau, P., Shively, T., & Kohn, R.
(1998). Estimating long-term trends in tropospheric ozone levels ( Department of Econometrics and Business Statistics Working Paper Series 02/98).Smith, M., & Kohn, R.
(1998). Nonparametric seemingly unrelated regression ( Department of Econometrics and Business Statistics Working Paper Series 07/98).Snyder, R., Koehler, A. B., & Ord, J. K.
(1998). Lead time demand for simple exponential smoothing ( Department of Econometrics and Business Statistics Working Paper Series 13/98).Strachan, R. W.
(1998). Bayesian estimation of the reduced rank regression model without ordering restrictions ( Department of Econometrics and Business Statistics Working Paper Series 09/98).Wong, Gary K. K.
(1998). A new approach to model GNP functions: An application of non-separable two-stage technologies ( Department of Econometrics and Business Statistics Working Paper Series 08/98).