Skip to main content

2012 | OriginalPaper | Buchkapitel

5. Panel Data, Factor Models, and the Solow Residual

verfasst von : Alois Kneip, Robin C. Sickles

Erschienen in: Exploring Research Frontiers in Contemporary Statistics and Econometrics

Verlag: Physica-Verlag HD

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

In this paper we discuss the Solow residual (Solow, Rev. Econ. Stat. 39:312–320, 1957) and how it has been interpreted and measured in the neoclassical production literature and in the complementary literature on productive efficiency. We point out why panel data are needed to measure productive efficiency and innovation and thus link the two strands of literatures. We provide a discussion on the various estimators used in the two literatures, focusing on one class of estimators in particular, the factor model. We evaluate in finite samples the performance of a particular factor model, the model of Kneip, Sickles, and Song (A New Panel Data Treatment for Heterogeneity in Time Trends, Econometric Theory, 2011), in identifying productive efficiencies. We also point out that the measurement of the two main sources of productivity growth, technical change and technical efficiency change, may be not be feasible in many empirical settings and that alternative survey based approaches offer advantages that have yet to be exploited in the productivity accounting literature.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Fußnoten
1
Since cross-sectional data are used, the efficiencies estimated are typically conditional expectations, as it is mentioned in Simar and Wilson (2010).
 
2
See Wolters Kluwer’s Aspen Press website for the Blue Chip Economic Indicators publication by Randell E. Moore:
 
3
We let \(\kappa = (1 - p)/p\) and chose p among a selected grid of 9 equally spaced values between 0.1 and 0.9 so that generalized cross-validation rule is minimized.
 
4
Although DGP1 consists of three different functions, [1, t, t 2], t 2 term is dominating as T gets large. Thus a one dimensional model is sufficient to approximate the effects generated by DGP1.
 
Literatur
Zurück zum Zitat Adams, R.M., Berger, A.N. & Sickles, R.C. (1999). Semiparametric approaches to stochastic panel frontiers with applications in the banking industry. Journal of Business and Economic Statistics, 17, 349–358. Adams, R.M., Berger, A.N. & Sickles, R.C. (1999). Semiparametric approaches to stochastic panel frontiers with applications in the banking industry. Journal of Business and Economic Statistics, 17, 349–358.
Zurück zum Zitat Adams, R.M., & Sickles, R.C. (2007). Semi-parametric efficient distribution free estimation of panel models. Communication in Statistics: Theory and Methods, 36, 2425–2442.MathSciNetMATHCrossRef Adams, R.M., & Sickles, R.C. (2007). Semi-parametric efficient distribution free estimation of panel models. Communication in Statistics: Theory and Methods, 36, 2425–2442.MathSciNetMATHCrossRef
Zurück zum Zitat Ahn, S.C., Lee, Y., & Schmidt, P.J. (2005). Panel data models with multiple time-varying individual effects: application to a stochastic frontier production model. mimeo, Michigan State University. Ahn, S.C., Lee, Y., & Schmidt, P.J. (2005). Panel data models with multiple time-varying individual effects: application to a stochastic frontier production model. mimeo, Michigan State University.
Zurück zum Zitat Aigner, D.J., Lovell, C.A.K., & Schmidt, P. (1977) Formulation and estimation of stochastic frontier models. Journal of Econometrics, 6, 21–37.MathSciNetMATHCrossRef Aigner, D.J., Lovell, C.A.K., & Schmidt, P. (1977) Formulation and estimation of stochastic frontier models. Journal of Econometrics, 6, 21–37.MathSciNetMATHCrossRef
Zurück zum Zitat Arrow K.J. (1962). The economic implications of learning by doing. Review of Economic Studies, 29, 155–173.CrossRef Arrow K.J. (1962). The economic implications of learning by doing. Review of Economic Studies, 29, 155–173.CrossRef
Zurück zum Zitat Battese, G.E., & Cora, G.S. (1977). Estimation of a production frontier model: with application to the pastoral zone of eastern Australia. Australian Journal of Agricultural Economics, 21, 169–179.CrossRef Battese, G.E., & Cora, G.S. (1977). Estimation of a production frontier model: with application to the pastoral zone of eastern Australia. Australian Journal of Agricultural Economics, 21, 169–179.CrossRef
Zurück zum Zitat Bai, J. (2005). Panel data models with interactive fixed effects. April 2005, mimeo, Department of Economics, New York University. Bai, J. (2005). Panel data models with interactive fixed effects. April 2005, mimeo, Department of Economics, New York University.
Zurück zum Zitat Bai, J., & Ng, S. (2007). Determining the number of primitive shocks in factor models. Journal of Business and Economic Statistics, 25, 52–60.MathSciNetCrossRef Bai, J., & Ng, S. (2007). Determining the number of primitive shocks in factor models. Journal of Business and Economic Statistics, 25, 52–60.MathSciNetCrossRef
Zurück zum Zitat Bai, J., Kao, C., & Ng, S. (2007). Panel cointegration with global stochastic trends. Center for Policy Research Working Papers 90, Center for Policy Research, Maxwell School, Syracuse University. Bai, J., Kao, C., & Ng, S. (2007). Panel cointegration with global stochastic trends. Center for Policy Research Working Papers 90, Center for Policy Research, Maxwell School, Syracuse University.
Zurück zum Zitat Balk, B. (2009). Price and quantity index numbers: models for measuring aggregate change and difference. New York: Cambridge University Press. Balk, B. (2009). Price and quantity index numbers: models for measuring aggregate change and difference. New York: Cambridge University Press.
Zurück zum Zitat Baltagi, B., Egger, P., & Pfaffermayr, M. (2003). A generalized design for bilateral trade flow models. Economics Letters, 80, 391–397.MathSciNetMATHCrossRef Baltagi, B., Egger, P., & Pfaffermayr, M. (2003). A generalized design for bilateral trade flow models. Economics Letters, 80, 391–397.MathSciNetMATHCrossRef
Zurück zum Zitat Baltagi, B. (2005). Econometric Analysis of Panel Data, 3rd edition, New Jersey: Wiley. Baltagi, B. (2005). Econometric Analysis of Panel Data, 3rd edition, New Jersey: Wiley.
Zurück zum Zitat Battese, G.E. & Coelli, T.J. (1992). Frontier production functions, technical efficiency and panel data: with application to paddy farmers in India. Journal of Productivity Analysis, 3, 153–169.CrossRef Battese, G.E. & Coelli, T.J. (1992). Frontier production functions, technical efficiency and panel data: with application to paddy farmers in India. Journal of Productivity Analysis, 3, 153–169.CrossRef
Zurück zum Zitat Berger, A.N. (1993). “Distribution-Free” estimates of efficiency in U.S. banking industry and tests of the standard distributional assumption. Journal of Productivity Analysis, 4, 261–292. Berger, A.N. (1993). “Distribution-Free” estimates of efficiency in U.S. banking industry and tests of the standard distributional assumption. Journal of Productivity Analysis, 4, 261–292.
Zurück zum Zitat Bernanke, B.S., & Boivin, J. (2003). Monetary policy in a data-rich environment. Journal of Monetary Economics, 50, 525–546.CrossRef Bernanke, B.S., & Boivin, J. (2003). Monetary policy in a data-rich environment. Journal of Monetary Economics, 50, 525–546.CrossRef
Zurück zum Zitat Blazek, D., & Sickles, R.C. (2010). The impact of knowledge accumulation and geographical spillovers on productivity and efficiency: the case of U.S. shipbuilding during WWII. In Hall, S.G., Klein, L.R., Tavlas, G.S. & Zellner, A. (eds.), Economic Modelling, 27, 1484–1497. Blazek, D., & Sickles, R.C. (2010). The impact of knowledge accumulation and geographical spillovers on productivity and efficiency: the case of U.S. shipbuilding during WWII. In Hall, S.G., Klein, L.R., Tavlas, G.S. & Zellner, A. (eds.), Economic Modelling, 27, 1484–1497.
Zurück zum Zitat Breitung, J., & Eickmeier, S. (2005). Dynamic factor models. Discussion Paper Series 1: Economic Studies, No 38/2005. Frankfurt: Deutsche Bundesbank. Breitung, J., & Eickmeier, S. (2005). Dynamic factor models. Discussion Paper Series 1: Economic Studies, No 38/2005. Frankfurt: Deutsche Bundesbank.
Zurück zum Zitat Breitung, J., & Kretschmer, U. (2005). Identification and estimation of dynamic factors from large macroeconomic panels. Mimeo: Universitat Bonn. Breitung, J., & Kretschmer, U. (2005). Identification and estimation of dynamic factors from large macroeconomic panels. Mimeo: Universitat Bonn.
Zurück zum Zitat Brumback, B.A., & Rice, J.A. (1998). Smoothing spline models for the analysis of nested and crossed samples of curves (with discussion). Journal of the American Statistical Association, 93, 961–94.MathSciNetMATHCrossRef Brumback, B.A., & Rice, J.A. (1998). Smoothing spline models for the analysis of nested and crossed samples of curves (with discussion). Journal of the American Statistical Association, 93, 961–94.MathSciNetMATHCrossRef
Zurück zum Zitat Caves, D., Christensen, L.R, & Diewert, W.E. (1982). Multilateral comparisons of output, input, and productivity using superlative index numbers. Economic Journal, 92, 73–86.CrossRef Caves, D., Christensen, L.R, & Diewert, W.E. (1982). Multilateral comparisons of output, input, and productivity using superlative index numbers. Economic Journal, 92, 73–86.CrossRef
Zurück zum Zitat Carriero, A., Kapetanios, G., & Marcellino, M. (2008). Forecasting large datasets with reduced rank multivariate models. Working Papers 617, Queen Mary, University of London, School of Economics and Finance. Carriero, A., Kapetanios, G., & Marcellino, M. (2008). Forecasting large datasets with reduced rank multivariate models. Working Papers 617, Queen Mary, University of London, School of Economics and Finance.
Zurück zum Zitat Chang, Y. (2004). Bootstrap unit root tests in panels with cross-sectional dependency. Journal of Econometrics, 120, 263–293.MathSciNetCrossRef Chang, Y. (2004). Bootstrap unit root tests in panels with cross-sectional dependency. Journal of Econometrics, 120, 263–293.MathSciNetCrossRef
Zurück zum Zitat Chamberlain, G., & Rothschild, M. (1983). Arbitrage, factor structure and mean-variance analysis in large asset markets. Econometrica, 51, 1305–1324.MathSciNetMATHCrossRef Chamberlain, G., & Rothschild, M. (1983). Arbitrage, factor structure and mean-variance analysis in large asset markets. Econometrica, 51, 1305–1324.MathSciNetMATHCrossRef
Zurück zum Zitat Charnes, A., Cooper, W.W., & Rhodes, E.L. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2, 429–444.MathSciNetMATHCrossRef Charnes, A., Cooper, W.W., & Rhodes, E.L. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2, 429–444.MathSciNetMATHCrossRef
Zurück zum Zitat Chun, A. (2009). Forecasting interest rates and inflation: blue chip clairvoyants or econometrics? EFA 2009 Bergen Meetings Paper, Bergen, Norway. Chun, A. (2009). Forecasting interest rates and inflation: blue chip clairvoyants or econometrics? EFA 2009 Bergen Meetings Paper, Bergen, Norway.
Zurück zum Zitat Cornwell, C., Schmidt, P., & Sickles, R.C. (1990). Production frontiers with cross-sectional and time-series variation in efficiency levels. Journal of Econometrics, 46, 185–200.CrossRef Cornwell, C., Schmidt, P., & Sickles, R.C. (1990). Production frontiers with cross-sectional and time-series variation in efficiency levels. Journal of Econometrics, 46, 185–200.CrossRef
Zurück zum Zitat Debreu, G. (1951). The coefficient of resource utilization. Econometrica, 19, 273–292.MATHCrossRef Debreu, G. (1951). The coefficient of resource utilization. Econometrica, 19, 273–292.MATHCrossRef
Zurück zum Zitat Diebold, F.X., & Li, C. (2006). Forecasting the term structure of government bond yields. Journal of Econometrics, 130, 337–364.MathSciNetCrossRef Diebold, F.X., & Li, C. (2006). Forecasting the term structure of government bond yields. Journal of Econometrics, 130, 337–364.MathSciNetCrossRef
Zurück zum Zitat Doz, C., Giannone, D., & Reichlin, L. (2006). A quasi maximum likelihood approach for large approximate dynamic factor models. ECB Working Paper 674. Doz, C., Giannone, D., & Reichlin, L. (2006). A quasi maximum likelihood approach for large approximate dynamic factor models. ECB Working Paper 674.
Zurück zum Zitat Engle, R., Granger, C., Rice, J., & Weiss, A. (1986). Nonparametric estimates of the relation between weather and electricity sales. Journal of American Statistical Association, 81, 310–320.CrossRef Engle, R., Granger, C., Rice, J., & Weiss, A. (1986). Nonparametric estimates of the relation between weather and electricity sales. Journal of American Statistical Association, 81, 310–320.CrossRef
Zurück zum Zitat Eubank, R.L. (1988). Nonparametric regression and spline smoothing. New York: Marcel Dekker.MATH Eubank, R.L. (1988). Nonparametric regression and spline smoothing. New York: Marcel Dekker.MATH
Zurück zum Zitat Färe, R., Grosskopf, S., Lindgren, B., & Roos, P. (1992). Productivity changes in Swedish pharamacies 1980–1989: a non-parametric Malmquist approach. Journal of Productivity Anlaysis, 3, 85–101.CrossRef Färe, R., Grosskopf, S., Lindgren, B., & Roos, P. (1992). Productivity changes in Swedish pharamacies 1980–1989: a non-parametric Malmquist approach. Journal of Productivity Anlaysis, 3, 85–101.CrossRef
Zurück zum Zitat Färe R., Grosskopf, S., Norris, M., & Zhang, Z. (1994). Productivity growth, technical progress and efficiency change in industrialized countries. American Economic Review, 84, 66–83. Färe R., Grosskopf, S., Norris, M., & Zhang, Z. (1994). Productivity growth, technical progress and efficiency change in industrialized countries. American Economic Review, 84, 66–83.
Zurück zum Zitat Farrell, M. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society, Series A, 120, 253–282.CrossRef Farrell, M. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society, Series A, 120, 253–282.CrossRef
Zurück zum Zitat Ferré, L. (1995). Improvement of some multivariate estimates by reduction of dimensionality. Journal of Multivariate Analysis, 54, 147–162.MathSciNetMATHCrossRef Ferré, L. (1995). Improvement of some multivariate estimates by reduction of dimensionality. Journal of Multivariate Analysis, 54, 147–162.MathSciNetMATHCrossRef
Zurück zum Zitat Fisher, I. (1927). The Making of Index Numbers. Boston: Houghton-Mifflin. Fisher, I. (1927). The Making of Index Numbers. Boston: Houghton-Mifflin.
Zurück zum Zitat Forni, M., & Lippi, M. (1997). Aggregation and the microfoundations of dynamic macroeconomics. Oxford: Oxford University Press.MATH Forni, M., & Lippi, M. (1997). Aggregation and the microfoundations of dynamic macroeconomics. Oxford: Oxford University Press.MATH
Zurück zum Zitat Forni, M., & Reichlin, L. (1998). Let’s get real: a factor analytic approach to disaggregated business cycle dynamics. Review of Economic Studies, 65, 653–473.CrossRef Forni, M., & Reichlin, L. (1998). Let’s get real: a factor analytic approach to disaggregated business cycle dynamics. Review of Economic Studies, 65, 653–473.CrossRef
Zurück zum Zitat Forni, M., Hallin, M., Lippi, M., & Reichlin, L. (2000). The generalized dynamic factor model: identification and estimation. Review of Economics and Statistics, 82, 540–554.CrossRef Forni, M., Hallin, M., Lippi, M., & Reichlin, L. (2000). The generalized dynamic factor model: identification and estimation. Review of Economics and Statistics, 82, 540–554.CrossRef
Zurück zum Zitat Førsund, F., & Hjalmarsson, L.(2008). Dynamic Analysis of Structural Change and Productivity Measurement. Unpublished Working Paper, Mimeo. Førsund, F., & Hjalmarsson, L.(2008). Dynamic Analysis of Structural Change and Productivity Measurement. Unpublished Working Paper, Mimeo.
Zurück zum Zitat Fried, H.O., Lovell, C.A.K., & Schmidt, S.S. (2008). The measurement of productive efficiency and productivity growth. Oxford University Press, Oxford.CrossRef Fried, H.O., Lovell, C.A.K., & Schmidt, S.S. (2008). The measurement of productive efficiency and productivity growth. Oxford University Press, Oxford.CrossRef
Zurück zum Zitat Getachew, L., & Sickles, R.C. (2007). Allocative distortions and technical efficiency change in Egypt’s private sector manufacturing industries: 1987–1996. Journal of the Applied Econometrics, 22, 703–728.MathSciNetCrossRef Getachew, L., & Sickles, R.C. (2007). Allocative distortions and technical efficiency change in Egypt’s private sector manufacturing industries: 1987–1996. Journal of the Applied Econometrics, 22, 703–728.MathSciNetCrossRef
Zurück zum Zitat Greene, W. (2004). Fixed and random effects in stochastic frontier models. Journal of Productivity Analysis, 23, 7–32.MathSciNetCrossRef Greene, W. (2004). Fixed and random effects in stochastic frontier models. Journal of Productivity Analysis, 23, 7–32.MathSciNetCrossRef
Zurück zum Zitat Greene, W. (2005). Reconsidering heterogeneity in panel data estimators of the stochastic frontier model. Journal of Econometrics, 126, 269–303.MathSciNetCrossRef Greene, W. (2005). Reconsidering heterogeneity in panel data estimators of the stochastic frontier model. Journal of Econometrics, 126, 269–303.MathSciNetCrossRef
Zurück zum Zitat Greene, W. (2008). In Fried, H., Lovell, C.A.K., & Schmidt, S. (eds.) The Measurement of Productive Efficiency and Productivity Change, Chap. 2. Oxford: Oxford University Press. Greene, W. (2008). In Fried, H., Lovell, C.A.K., & Schmidt, S. (eds.) The Measurement of Productive Efficiency and Productivity Change, Chap. 2. Oxford: Oxford University Press.
Zurück zum Zitat Härdle, W., Liang, H., & Gao, J. (2000). Partially linear models. Heidelberg: Physica-Verlag.MATHCrossRef Härdle, W., Liang, H., & Gao, J. (2000). Partially linear models. Heidelberg: Physica-Verlag.MATHCrossRef
Zurück zum Zitat Jeon, B.M., & Sickles, R.C. (2004). The Role of environmental factors in growth accounting: a nonparametric analysis. Journal of the Applied Economics, 19, 567–591.CrossRef Jeon, B.M., & Sickles, R.C. (2004). The Role of environmental factors in growth accounting: a nonparametric analysis. Journal of the Applied Economics, 19, 567–591.CrossRef
Zurück zum Zitat Jorgenson, D.W., & Griliches, Z. (1972). Issues in growth accounting: a reply to Edward F. Denison. Survey of Current Business, 55 (part 2), 65–94. Jorgenson, D.W., & Griliches, Z. (1972). Issues in growth accounting: a reply to Edward F. Denison. Survey of Current Business, 55 (part 2), 65–94.
Zurück zum Zitat Kao, C., & Chiang, M.H. (2000). On the estimation and inference of a cointegrated regression in panel data. Advances in Econometrics, 15, 179–222.MathSciNetCrossRef Kao, C., & Chiang, M.H. (2000). On the estimation and inference of a cointegrated regression in panel data. Advances in Econometrics, 15, 179–222.MathSciNetCrossRef
Zurück zum Zitat Kapetanios, G., & Marcellino, M., (2009). A parametric estimation method for dynamic factor models of large dimensions, Journal of Time Series Analysis, 30, 208–238.MathSciNetCrossRef Kapetanios, G., & Marcellino, M., (2009). A parametric estimation method for dynamic factor models of large dimensions, Journal of Time Series Analysis, 30, 208–238.MathSciNetCrossRef
Zurück zum Zitat Klee, E.C., & Natalucci, F.M. (2005). Profits and balance sheet developments at U.S. commercial banks in 2004. Federal Reserve Bulletin, Spring. Klee, E.C., & Natalucci, F.M. (2005). Profits and balance sheet developments at U.S. commercial banks in 2004. Federal Reserve Bulletin, Spring.
Zurück zum Zitat Kendrick, J. (1961). Productivity trends in the United States. Princeton: Princeton University Press for the National Bureau of Economic Research. Kendrick, J. (1961). Productivity trends in the United States. Princeton: Princeton University Press for the National Bureau of Economic Research.
Zurück zum Zitat Koop, G.M., & Poirier, D. (2004). Bayesian variants of some classical semiparametric regression techniques. Journal of Econometrics, 123(2), 259–282.MathSciNetMATHCrossRef Koop, G.M., & Poirier, D. (2004). Bayesian variants of some classical semiparametric regression techniques. Journal of Econometrics, 123(2), 259–282.MathSciNetMATHCrossRef
Zurück zum Zitat Kneip, A. (1994). Nonparametric estimation of common regressors for similar curve data. Annals of Statistics, 22, 1386–1427.MathSciNetMATHCrossRef Kneip, A. (1994). Nonparametric estimation of common regressors for similar curve data. Annals of Statistics, 22, 1386–1427.MathSciNetMATHCrossRef
Zurück zum Zitat Kneip, A., & Utikal, K.J. (2001). Inference for density families using functional principal component analysis. Journal of American Statistical Association, 96, 519–532.MathSciNetMATHCrossRef Kneip, A., & Utikal, K.J. (2001). Inference for density families using functional principal component analysis. Journal of American Statistical Association, 96, 519–532.MathSciNetMATHCrossRef
Zurück zum Zitat Kneip, A., Sickles, R.C., & Song, W. (2011). A new panel data treatment for heterogeneity in time trends. Econometric Theory, to appear. Kneip, A., Sickles, R.C., & Song, W. (2011). A new panel data treatment for heterogeneity in time trends. Econometric Theory, to appear.
Zurück zum Zitat Kumbhakar, S.C. (1990). Production Frontiers, panel data and time-varying technical inefficiency. Journal of Econometrics, 46, 201–211.CrossRef Kumbhakar, S.C. (1990). Production Frontiers, panel data and time-varying technical inefficiency. Journal of Econometrics, 46, 201–211.CrossRef
Zurück zum Zitat Kumbhakar, S., & Lovell, C.A.K. (2000). Stochastic Frontier Analysis. Cambridge: Cambridge University Press.MATHCrossRef Kumbhakar, S., & Lovell, C.A.K. (2000). Stochastic Frontier Analysis. Cambridge: Cambridge University Press.MATHCrossRef
Zurück zum Zitat Lovell, C.A.K., Richardson, S., Travers, P., & Wood, L.L. (1994). Resources and functionings: a new view of inequality in Australia. In Eichorn, W. (Ed.) Models and Measurement of Welfare and Inequality, pp. 787–807. Berlin, Heidelberg, New York: Springer.CrossRef Lovell, C.A.K., Richardson, S., Travers, P., & Wood, L.L. (1994). Resources and functionings: a new view of inequality in Australia. In Eichorn, W. (Ed.) Models and Measurement of Welfare and Inequality, pp. 787–807. Berlin, Heidelberg, New York: Springer.CrossRef
Zurück zum Zitat Lucas, R.E. (1988). On the Mechanics of Economic Development. Journal of Monetary Economics, 22, 3–42.CrossRef Lucas, R.E. (1988). On the Mechanics of Economic Development. Journal of Monetary Economics, 22, 3–42.CrossRef
Zurück zum Zitat Maddala, G.S., & Kim, I.M. (1998). Unit Roots, cointegration and structural change. Cambridge: Cambridge University Press. Maddala, G.S., & Kim, I.M. (1998). Unit Roots, cointegration and structural change. Cambridge: Cambridge University Press.
Zurück zum Zitat Mark, N.C., & Sul, D. (2003). Cointegration vector estimation by panel dlos and long-run money demand. Oxford Bulletin of Economics and Statistics, 65, 655–680.CrossRef Mark, N.C., & Sul, D. (2003). Cointegration vector estimation by panel dlos and long-run money demand. Oxford Bulletin of Economics and Statistics, 65, 655–680.CrossRef
Zurück zum Zitat Marcellino, M., & Schumacher, C. (2007). Factor-midas for now- and forecasting with ragged-edge data: a model comparison for German gdp. Discussion Paper Series 1: Economic Studies,34, Deutsche Bundesbank, Research Centre. Marcellino, M., & Schumacher, C. (2007). Factor-midas for now- and forecasting with ragged-edge data: a model comparison for German gdp. Discussion Paper Series 1: Economic Studies,34, Deutsche Bundesbank, Research Centre.
Zurück zum Zitat Meeusen, W., & van den Broeck, J. (1977). Efficiency estimation from Cobb-Douglas production functions with composed error. International Economic Review, 18, 435–444.MATHCrossRef Meeusen, W., & van den Broeck, J. (1977). Efficiency estimation from Cobb-Douglas production functions with composed error. International Economic Review, 18, 435–444.MATHCrossRef
Zurück zum Zitat Nelson, C.R., & Plosser, C.I. (1982). Trends and random walks in macroeconomics time series: some evidence and implications. Journal of Monetary Economics, 10, 139–162.CrossRef Nelson, C.R., & Plosser, C.I. (1982). Trends and random walks in macroeconomics time series: some evidence and implications. Journal of Monetary Economics, 10, 139–162.CrossRef
Zurück zum Zitat Orea, C., & Kumbhakar, S. (2004). Efficiency measurement using a latent class stochastic frontier model. Empirical Economics, 29, 169–184.CrossRef Orea, C., & Kumbhakar, S. (2004). Efficiency measurement using a latent class stochastic frontier model. Empirical Economics, 29, 169–184.CrossRef
Zurück zum Zitat Park, B.U., & Simar, L. (1994). Efficient semiparametric estimation in stochastic frontier models. Journal of the American Statistical Association, 89, 929–936.MathSciNetMATHCrossRef Park, B.U., & Simar, L. (1994). Efficient semiparametric estimation in stochastic frontier models. Journal of the American Statistical Association, 89, 929–936.MathSciNetMATHCrossRef
Zurück zum Zitat Park, B.U., Sickles, R.C., & Simar, L. (1998). Stochastic frontiers: a semiparametric approach. Journal of Econometrics, 84, 273–301.MathSciNetMATHCrossRef Park, B.U., Sickles, R.C., & Simar, L. (1998). Stochastic frontiers: a semiparametric approach. Journal of Econometrics, 84, 273–301.MathSciNetMATHCrossRef
Zurück zum Zitat Park, B.U., Sickles, R.C., & Simar, L. (2003). Semiparametric efficient estimation of AR(1) panel data models. Journal of Econometrics, 117, 279–309.MathSciNetMATHCrossRef Park, B.U., Sickles, R.C., & Simar, L. (2003). Semiparametric efficient estimation of AR(1) panel data models. Journal of Econometrics, 117, 279–309.MathSciNetMATHCrossRef
Zurück zum Zitat Park, B.U., Sickles, R.C., & Simar, L. (2007). Semiparametric efficient estimation of dynamic panel data models. Journal of Econometrics, 136, 281–301.MathSciNetCrossRef Park, B.U., Sickles, R.C., & Simar, L. (2007). Semiparametric efficient estimation of dynamic panel data models. Journal of Econometrics, 136, 281–301.MathSciNetCrossRef
Zurück zum Zitat Pesaran, M.H. (2006). Estimation and inference in large heterogeneous panels with a multifactor error structure. Econometrica, 74, 967–1012.MathSciNetMATHCrossRef Pesaran, M.H. (2006). Estimation and inference in large heterogeneous panels with a multifactor error structure. Econometrica, 74, 967–1012.MathSciNetMATHCrossRef
Zurück zum Zitat Pitt, M., & Lee, L.-F. (1981). The measurement and sources of technical inefficiency in the Indonesian weaving industry. Journal of Development Economics, 9, 43–64.CrossRef Pitt, M., & Lee, L.-F. (1981). The measurement and sources of technical inefficiency in the Indonesian weaving industry. Journal of Development Economics, 9, 43–64.CrossRef
Zurück zum Zitat Ramsay, J., & Silverman, B. (1997). Functional data analysis. Heidelberg: Springer.MATH Ramsay, J., & Silverman, B. (1997). Functional data analysis. Heidelberg: Springer.MATH
Zurück zum Zitat Rao, C.R. (1958). Some statistical methods for the comparison of growth curves. Biometrics, 14, 1–17.MATHCrossRef Rao, C.R. (1958). Some statistical methods for the comparison of growth curves. Biometrics, 14, 1–17.MATHCrossRef
Zurück zum Zitat Reikard, G. (2005). Endogenous technical advance and the stochastic trend in output: A neoclassical approach. Research Policy, 34, 1476–1490.CrossRef Reikard, G. (2005). Endogenous technical advance and the stochastic trend in output: A neoclassical approach. Research Policy, 34, 1476–1490.CrossRef
Zurück zum Zitat Romer, P.M. (1986). Increasing returns and long-run growth. Journal of Political Economy, 94, 1002–1037.CrossRef Romer, P.M. (1986). Increasing returns and long-run growth. Journal of Political Economy, 94, 1002–1037.CrossRef
Zurück zum Zitat Schmidt, P., & Sickles, R.C. (1984). Production frontiers and panel data. Journal of Business and Economic Statistics, 2, 367–374. Schmidt, P., & Sickles, R.C. (1984). Production frontiers and panel data. Journal of Business and Economic Statistics, 2, 367–374.
Zurück zum Zitat Sickles, R.C., & Streitwieser, M. (1992). Technical inefficiency and productive decline in the U.S. interstate natural gas pipeline industry under the U.S. interstate natural gas policy act. Journal of Productivity Analysis (Lewin, A., & Lovell, C.A.K. Eds.), 3, 115–130. Reprinted in International Applications for Productivity and Efficiency Analysis, (Thomas R. Gulledge, Jr., & Knox Lovell, C.A. Eds.). Boston: Kluwer. Sickles, R.C., & Streitwieser, M. (1992). Technical inefficiency and productive decline in the U.S. interstate natural gas pipeline industry under the U.S. interstate natural gas policy act. Journal of Productivity Analysis (Lewin, A., & Lovell, C.A.K. Eds.), 3, 115–130. Reprinted in International Applications for Productivity and Efficiency Analysis, (Thomas R. Gulledge, Jr., & Knox Lovell, C.A. Eds.). Boston: Kluwer.
Zurück zum Zitat Sickles, R.C., & Streitwieser, M. (1998). The structure of technology, substitution and productivity in the interstate natural gas transmission industry under the natural gas policy act of l978. Journal of Applied Econometrics, 13, 377–395.CrossRef Sickles, R.C., & Streitwieser, M. (1998). The structure of technology, substitution and productivity in the interstate natural gas transmission industry under the natural gas policy act of l978. Journal of Applied Econometrics, 13, 377–395.CrossRef
Zurück zum Zitat Sickles, R.C. (2005). Panel estimators and the identification of firm-specific efficiency levels in parametric, semiparametric and nonparametric settings. Journal of Econometrics, 50, 126, 305–334. Sickles, R.C. (2005). Panel estimators and the identification of firm-specific efficiency levels in parametric, semiparametric and nonparametric settings. Journal of Econometrics, 50, 126, 305–334.
Zurück zum Zitat Sickles, R.C., & Tsionas, E.G. (2008). A panel data model with nonparametric time effects. Mimeo: Rice University. Sickles, R.C., & Tsionas, E.G. (2008). A panel data model with nonparametric time effects. Mimeo: Rice University.
Zurück zum Zitat Simar, L., & Wilson, P.W. (2010). Inference from cross-sectional stochastic frontier models. Econometric Reviews, 29, 62–98.MathSciNetMATHCrossRef Simar, L., & Wilson, P.W. (2010). Inference from cross-sectional stochastic frontier models. Econometric Reviews, 29, 62–98.MathSciNetMATHCrossRef
Zurück zum Zitat Shephard, R.W. (1970). Theory of cost and production functions. Princeton: Princeton University Press.MATH Shephard, R.W. (1970). Theory of cost and production functions. Princeton: Princeton University Press.MATH
Zurück zum Zitat Solow, Robert M. (1957). Technical change and the aggregate production function. Review of Economics and Statistics, 39, 312–320.CrossRef Solow, Robert M. (1957). Technical change and the aggregate production function. Review of Economics and Statistics, 39, 312–320.CrossRef
Zurück zum Zitat Speckman, P. (1988). Kernel smoothing in partial linear models. Journal of the Royal Statistical Society, Series B, 50, 413–436.MathSciNetMATH Speckman, P. (1988). Kernel smoothing in partial linear models. Journal of the Royal Statistical Society, Series B, 50, 413–436.MathSciNetMATH
Zurück zum Zitat Stock, J.H., & Watson, M.W. (2002). Forecasting using principal components from a large number of predictors. Journal of the American Statistical Association, 97, 1167–1179.MathSciNetMATHCrossRef Stock, J.H., & Watson, M.W. (2002). Forecasting using principal components from a large number of predictors. Journal of the American Statistical Association, 97, 1167–1179.MathSciNetMATHCrossRef
Zurück zum Zitat Stock, J.H., & Watson, M.W. (2005). Implications of dynamic factor models for VAR analysis. Mimeo: Princeton University.CrossRef Stock, J.H., & Watson, M.W. (2005). Implications of dynamic factor models for VAR analysis. Mimeo: Princeton University.CrossRef
Zurück zum Zitat Tsionas, E.G., & Greene, W. (2003). A panel data model with nonparametric time effects, Athens University of Business and Economics. Tsionas, E.G., & Greene, W. (2003). A panel data model with nonparametric time effects, Athens University of Business and Economics.
Metadaten
Titel
Panel Data, Factor Models, and the Solow Residual
verfasst von
Alois Kneip
Robin C. Sickles
Copyright-Jahr
2012
Verlag
Physica-Verlag HD
DOI
https://doi.org/10.1007/978-3-7908-2349-3_5