| Reference: | Adler, G., Duval, R. A., Furceri, D., Çelik, S. K., Koloskova, K., & Poplawski-Ribeiro, M.(2017). Gone with the headwinds: Global productivity. International Monetary Fund.
Allison, P. D. (2009). Fixed Effects Regression Models. SAGE Publications.
Alviarez, V., Cravino, J., & Ramondo, N. (2023). Firm-embedded productivity and cross-country income differences. Journal of Political Economy, 131(9), 2289-2327.
An, X., Yang, Q., & Bentler, P. M. (2013). A latent factor linear mixed model for high-dimensional longitudinal data analysis. Statistics in Medicine, 32(24), 4229-4239.
Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist’s Companion. Princeton University Press.
Banerjee, A. V., & Duflo, E. (2005). Growth theory through the lens of development economics.
Handbook of Economic Growth, 1, 473-552.
Banerjee, A. V., & Moll, B. (2010). Why does misallocation persist?. American Economic Journal: Macroeconomics, 2(1), 189-206.
Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51(6),1173-1182.
Barro, R. J., & Sala-i-Martin, X. (1992). Convergence. Journal of Political Economy, 100(2), 223-251.
Barro, R. J., Sala-i-Martin, X. (2004). Economic Growth (2nd ed.). MIT Press.
Bauer, D. J., Preacher, K. J., & Gil, K. M. (2006). Conceptualizing and testing random indirect effects and moderated mediation in multilevel models: new procedures and recommendations. Psychological Methods, 11(2), 142– 163. https://doi.org/10.1037/1082-989X.11.2.142
Bates, D., Mächler, M., Bolker, B., & Walker, S.(2015). Fitting Linear Mixed-Effects Models Using lme4. Journal of Statistical Software, 67(1),1-48.
Bils, M., Klenow, P. J., & Ruane, C. (2021). Misallocation or mismeasurement? Journal of Monetary Economics, 124, S39-S56.
Blood, E. A., & Cheng, D. M. (2011). The use of mixed models for the analysis of mediated data with time-dependent predictors. Journal of Environmental and Public Health,Article 2011.https://doi.org/10.1155/2011/435078。
Bollen, K. A., Harden, J. J., Ray, S., & Zavisca, J. (2014). BIC and alternative Bayesian information criteria in the selection of structural equation models. Structural Equation Modeling, 21(1), 1-19. https://doi.org/10.1080/10705511.2014.856691
Buera, F. J., Kaboski, J. P., & Shin, Y. (2011). Finance and development: A tale of two sectors. American Economic Review, 101(5), 1964-2002.
Buera, F. J., & Shin, Y. (2013). Financial frictions and the persistence of history: A quantitative exploration. Journal of Political Economy, 121(2), 221–272. https://doi.org/10.1086/670271
Busso, M., Madrigal, L., & Pagés, C. (2012). Productivity and resource misallocation in latin america. The BE Journal of Macroeconomics, 13(1), 903-932.
Cashin, A. G., & Lee, H. (2021). An introduction to mediation analyses of randomized controlled trials. Journal of Clinical Epidemiology, 131,161-164.
Cheung, M. W.-L. (2007). Comparison of approaches to constructing confidence intervals for mediating effects using structural equation models. Structural Equation Modeling: A Multidisciplinary Journal, 14(2),227– 246.
Cole, D. A., & Maxwell, S. E. (2003). Testing mediational models with longitudinal data: questions and tips in the use of structural equation modeling. Journal of Abnormal Psychology, 112(4), 558-577.
International Monetary Fund. (2015). Causes and consequences of income inequality: A global perspective. IMF Staff Discussion Note, SDN/15/13. https://www.imf.org/external/pubs/ft/sdn/2015/sdn1513.pdf
Delattre, M., Lavielle, M., & Poursat, M. A. (2014). A note on BIC in mixed-effects models. Electronic Journal of Statistics, 8(1), 456-475.
Demirer, M. (2020). Production function estimation with factor-augmenting technology: An application to markups. Job Market Paper.
Dempster, A. P., Laird, N. M., & Rubin, D. B. (1977). Maximum likelihood from incomplete data via the EM algorithm. Journal of the Royal Statistical Society: Series B (Methodological), 39(1), 1-38.
Diggle, P. J., Heagerty, P., Liang, K. Y., & Zeger, S. L. (2002). Analysis of Longitudinal Data(2nd ed.). Oxford University Press.
Eberly, J. C., Rebelo, S., & Vincent, N. (2012). What explains the lagged investment effect? Journal of Monetary Economics, 59(4), 370– 380. https://doi.org/10.1016/j.jmoneco.2012.04.006
Fan, S., & Zhang, X. (2004). Infrastructure and regional economic development in rural China. China Economic Review, 15(2), 203-214.
Fisher, R.A. (1925). Statistical Methods for Research Workers. Edinburgh: Oliver and Boyd. Fitzmaurice, G. M., Laird, N. M., & Ware, J. H. (2011). Applied Longitudinal Analysis (2nd ed.). Wiley.
Gennaioli, N., La Porta, R., Lopez-de-Silanes, F., Shleifer, A. (2014). Growth in regions. Journal of Economic Growth, 19(3), 259– 309.
Gandhi, A., Navarro, S., & Rivers, D. A. (2020). On the identification of gross output production functions. Journal of Political Economy, 12(8), 2973-3016.
Gelman, A., Carlin, J. B., Stern, H. S.,Dunson, D. B., Vehtari, A., & Rubin, D. B.(2013). Bayesian Data Analysis(3rd ed.). Chapman and Hall/CRC.
Gelman, A., & Hill, J. (2007). Data Analysis Using Regression and Multilevel/Hierarchical Models. Cambridge University Press.
Goldstein, H. (2011) Multilevel Statistical Models.Multilevel Statistical Models. New Jersey: John Wiley & Sons.
Hall, R. E., & Jones, C. I. (1999). Why do some countries produce so much more output per worker than others? The Quarterly Journal of Economics, 114(1), 83-116.
Hedeker, D., & Gibbons, R. D. (2006). Longitudinal Data Analysis. New Jersey: John Wiley & Sons
Hirschfeld, G., & Brachel, R. (2014). Multiple-Group confirmatory factor analysis in R – A tutorial in measurement invariance with continuous and ordinal indicators. Practical Assessment, Research & Evaluation, 19, 1-12. https://doi.org/10.7275/qazy-2946
Hox, J. J.(2010). Multilevel Analysis:Techniques and Applications(2nd ed.). Routledge.
Hsieh, C.-T., & Klenow, P. (2009). Misallocation and manufacturing tfp in China and India. Quarterly Journal of Economics, 124(4), 1403-1448.
Hsieh, C.-T., & Moretti, E. (2019). Housing constraints and spatial misallocation. American Economic Journal: Macroeconomics, 11(2), 1-39.
Jones, C. I. (2013). Misallocation, input-output economics, and economic growth. In Advances in Economics and Econometrics: Tenth World Congress (Vol. 2, pp. 419-458). Cambridge University Press.
Jose, P. E. (2016). Doing Statistical Mediation and Moderation. New York, NY: Guilford Press.
Jovanovic, B. (2014). Misallocation and growth. American Economic Review, 104(4), 1149-1171.
Kim, E. S., Cao, C., Wang, Y., & Nguyen, D. T. (2017). Measurement invariance testing with many groups: a comparison of five approaches. Structural Equation Modeling: A Multidisciplinary Journal, 24(4), 524-544. https://doi.org/10.1080/10705511.2017.1304822
Klenow, P. J., & Rodriguez-Clare, A. (1997). The neoclassical revival in growth economics: Has it gone too far? NBER Macroeconomics Annual, 12, 73-103.
Laird, N. M., & Ware, J. H. (1982). Random-effects models for longitudinal data. Biometrics, 38(4), 963– 974.
Li, S., E, H., Wang, L., & Xue, H. (2023). Factor misallocation and optimization in China’s manufacturing industry. Sustainability, 15(5), 4279.
Liang, K.-Y., & Zeger, S. L. (1986). Longitudinal data analysis using generalized linear models.
Biometrika, 73(1), 13– 22.
Maas, C. J. M., & Hox, J. J.(2005). Sufficient sample sizes for multilevel modeling. Methodology: European Journal of Research Methods for the Behavioral and Social Sciences, 1(3),86-92.
MacKinnon, D. P. (2008). Introduction to Statistical Mediation Analysis. Lawrence Erlbaum Associates.
MacKinnon, D. P., Fairchild, A. J., & Fritz, M. S. (2007). Mediation analysis. Annual Review of Psychology, 58, 593– 614.
MacKinnon, D. P., Lockwood, C. M., & Williams, J. (2004). Confidence limits for the indirect effect: distribution of the product and resampling methods.Multivariate Behavioral Research, 39(1), 99-128.
Markovits, R. S. (1975). The causes and policy significance of pareto resource misallocation: a checklist for micro-economic policy analysis. Stanford Law Review, 28(1), 1-46.
McLachlan, G., Peel, D., & Bean, R. (2003). Modelling high-dimensional data by mixtures of factor analyzers. Computational Statistics & Data Analysis, 41(3), 379-388. https://doi.org/10.1016/S0167-9473(02)00183-4
Meredith, W., & Horn, J. L. (2001). The role of measurement invariance in understanding group differences in multivariate data. Multivariate Behavioral Research, 36(3), 527–552.
Midrigan, V., & Xu, D. Y. (2014). Finance and misallocation: Evidence from plant-level data. American Economic Review, 104(2), 422-458.
Millsap, R. E. (2011). Statistical Approaches to Measurement Invariance. Routledge.
Moll, B. (2014). Productivity losses from financial frictions：can self-financing undo capital misallocation? American Economic Review, 104(10), 3186-3221.
Ounajim, A., Slaoui, Y., Louis, P.-Y., Billot, M., Frasca, D., & Rigoard, P. (2023). Mixture of longitudinal factor analyzers and their application to the assessment of chronic pain. Statistics in Medicine, 42(18), 3259– 3282. https://doi.org/10.1002/sim.9804
Parente, S. L., & Prescott, E. C. (1994). Barriers to technology adoption and development. Journal of Political Economy, 102(2), 298-321.
Parente, S. L., & Prescott, E. C. (1999). Monopoly rights: A barrier to riches. American Economic Review, 89(5), 1216-1233.
Pearl, J. (2009). Causality: Models, Reasoning, and Inference. Cambridge University Press.
Pinheiro, J. C., & Bates, D. M.(2000). Mixed-Effects Models in S and S-PLUS. New York:Springer.
Preacher, K. J., Curran, P. J., & Bauer, D. J. (2006). Computational tools for probing interactions in multiple linear regression, multilevel modeling, and latent curve analysis. Journal of Educational and Behavioral Statistics, 34(1),437– 448.
Preacher, K. J., & Hayes, A. F. (2004). SPSS and SAS procedures for estimating indirect effects in simple mediation models. Behavior Research Methods, Instruments, & Computers, 36(4),717-731.
Proust, C., Jacqmin-Gadda, H., Taylor, J. M. G., Ganiayre, J., & Commenges, D. (2006). A nonlinear model with latent process for cognitive evolution using multivariate longitudinal data. Biometrics, 62(4), 1014-1024. https://doi.org/10.1111/j.1541-0420.2006.00573.x
Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical Linear Models: Applications and Data Analysis Methods(2nd ed.). Thousand Oaks, CA: Sage Publications.
Restuccia, D., & Rogerson, R. (2008). Policy distortions and aggregate productivity with heterogeneous establishments. Review of Economic Dynamics, 11(4), 707-720.
Restuccia, D., & Rogerson, R. (2017). The causes and costs of misallocation. Journal of Economic Perspectives, 31(3), 151-174.
Rijnhart, J. J. M., Twisk, J. W. R., Valente, M. J., & Heymans, M. W. (2022). Time lags and time interactions in mixed effects models impacted longitudinal mediation effect estimates.
Journal of Clinical Epidemiology, 151, 143-150. https://doi.org/10.1016/j.jclinepi.2022.07.004
Rodrigue, J., Shi, Q., & Tan, Y. (2024). Trade policy uncertainty & resource misallocation. European Economic Review, 164, 104720.
Rodríguez-Pose, A. (2018). The revenge of the places that don’t matter (and what to do about it). Cambridge Journal of Regions, Economy and Society, 11(1), 189-209.
Rohrer, J. M. (2018). Thinking clearly about correlations and causation: Graphical causal models for observational data. Advances in Methods and Practices in Psychological Science, 1(1), 27– 42.
Rotemberg, M., & White, T. K. (2021). Plant‐to‐Table(s and Figures): Processed Manufacturing Data and Measured Misallocation. Mimeo.
Roy, J., & Lin, X. (2000). Latent variable models for longitudinal data with multiple continuous outcomes. Biometrics, 56(4),1047-1054.
Schwarz, G. (1978). Estimating the dimension of a model. The Annals of Statistics, 6(2), 461– 464.
Singer, J. D., & Willett, J. B. (2003). Applied Longitudinal Data Analysis: Modeling Change and Event Occurrence. Oxford University Press.
Snijders, T. A. B., & Bosker, R. J. (2012). Multilevel Analysis: An Introduction to Basic and Advanced Multilevel Modeling (2nd ed.). Sage.
Spearman, C. (1904). ”General intelligence,” objectively determined and measured. American Journal of Psychology, 15(2),201-292.
Twisk, J. W. R. (2013). Applied Longitudinal Data Analysis for Epidemiology: A Practical Guide. Cambridge, United Kingdom: Cambridge University Press.
Uras, B. R. (2014). Journal of Banking & Finance, 39, 177-191. Corporate financial structure, misallocation and total factor productivity.
West, B. T., Welch, K. B., & Galecki, A. T.(2014). Linear Mixed Models:A Practical Guide Using Statistical Software. Chapman and Hall/CRC.
Wooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data (2nd ed.). The MIT Press. |
