This paper presents a new approach to estimation and inference in panel data models with a multifactor error structure where the unobserved common factors are (possibly) correlated with exogenously given individual-specific regressors, and the factor loadings differ over the cross section units. The basic idea behind the proposed estimation procedure is to filter the individual-specific regressors by means of (weighted) cross-section aggregates such that asymptotically as the cross-section dimension (N) tends to infinity the differential effects of unobserved common factors are eliminated. The estimation procedure has the advantage that it can be computed by OLS applied to an auxiliary regression where the observed regressors are augmented by (weighted) cross sectional averages of the dependent variable and the individual specific regressors. Two different but related problems are addressed: one that concerns the coefficients of the individual-specific regressors, and the other that focusses on the mean of the individual coefficients assumed random. In both cases appropriate estimators, referred to as common correlated effects (CCE) estimators, are proposed and their asymptotic distribution as N with T (the time-series dimension) fixed or as N and T (jointly) are derived under different regularity conditions. One important feature of the proposed CCE mean group (CCEMG) estimator is its invariance to the (unknown but fixed) number of unobserved common factors as N and T (jointly). The small sample properties of the various pooled estimators are investigated by Monte Carlo experiments that confirm the theoretical derivations and show that the pooled estimators have generally satisfactory small sample properties even for relatively small values of N and T.

Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure

Does culture have a causal effect on economic development? The data on European regions suggest that it does. Culture is measured by indicators of individual values and beliefs, such as trust and respect for others, and confidence in individual self determination. To isolate the exogenous variation in culture, we rely on two historical variables used as instruments: the literacy rate at the end of the 19th century, and the political institutions in place over the past several centuries. The political and social history of Europe provides a rich source of variation in these two variables at a regional level. The exogenous component of culture due to history is strongly correlated with current regional economic development, after controlling for contemporaneous education, urbanization rates around 1850, and national effects. (JEL: O10, F10, P10, N13)

https://www.ifs.org.uk/conferences/tabellini.pdf

Culture and institutions: economic development in the regions of europe

This paper proposes a modified version of Swamy's test of slope homogeneity for panel data models where the cross section dimension (N) could be large relative to the time series dimension (T). The proposed test exploits the cross section dispersion of individual slopes weighted by their relative precision. In the case of models with strictly exogenous regressors and normally distributed errors, the test is shown to have a standard normal distribution. Using Monte Carlo experiments, it is shown that the test has the correct size and satisfactory power in panels with strictly exogenous regressors for various combinations of N and T. For autoregressive (AR) models the proposed test performs well for moderate values of the root of the autoregressive process. But for AR models with roots near unity a bias-corrected bootstrapped version of the test is proposed which performs well even if N is large relative to T. The proposed cross section dispersion tests are applied to testing the homogeneity of slopes in autoregressive models of individual earnings using the PSID data. The results show statistically significant evidence of slope heterogeneity in the earnings dynamics, even when individuals with similar educational backgrounds are considered as sub-sets.

Testing Slope Homogeneity in Large Panels

This paper surveys the convergence literature. It begins by laying out different definitions of convergence and by showing the link between the convergence issue and the growth theory debate. The paper then follows the convergence research conducted along four different approaches, namely the cross-section, panel, time-series, and distribution approaches. The paper shows the association of these methodological approaches with various definitions of convergence and highlights the connections among the convergence results. It shows that, despite some impressions to the contrary, there is considerable agreement among the results. Although the convergence research might not have solved the growth debate entirely, it has helped both the neoclassical and the new growth theories to adapt and evolve. The research on convergence has established new stylized facts regarding cross-country growth regularities. It has brought to fore the existence of large technological and institutional differences across countries and has given rise to new methodologies for quantifying and analyzing these differences. This is providing a new information base for analysis of technological and institutional diffusion and for further development of growth theory in general.

/pdf/what-have-we-learnt-from-the-convergence-debate-1bfeple9tg.pdf

What have We Learnt from the Convergence Debate

https://www.econstor.eu/bitstream/10419/74513/1/cesifo_wp4232.pdf

Common Correlated Effects Estimation of Heterogeneous Dynamic Panel Data Models with Weakly Exogenous Regressors

This paper presents a global model linking individual country vector error-correcting models in which the domestic variables are related to the country-specific variables as an approximate solution to a global common factor model. This global VAR is estimated for 26 countries, the euro area being treated as a single economy. This paper proposes two important extensions of previous research (see Pesaran, Schuermann and Weiner, 2004). First, it provides a theoretical framework where the GVAR is derived as an approximation to a global unobserved common factor model. Also using average pair-wise cross-section error correlations, the GVAR approach is shown to be quite effective in dealing with the common factor interdependencies and international comovements of business cycles. Second, in addition to generalised impulse response functions, we propose an identification scheme to derive structural impulse responses. We focus on identification of shocks to the US economy, particularly the monetary policy shocks, and consider the time profiles of their effects on the euro area. To this end we include the US model as the first country model and consider alternative orderings of the US variables. Further to the US monetary policy shock, we also consider oil price, US equity and US real output shocks.

Exploring the International Linkages of the Euro Area: a Global VAR Analysis

It is now quite common to have panels in which T, the number of time series observations on the N groups, is quite large The usual practice is either to estimate N separate regressions and calculate the mean, which we call the Mean Group estimator, or to pool the data and assume the slope coefficients and variances are identical In this paper, the authors propose an intermediate procedure, referred to as the Pooled Mean Group (PMG) estimator, which constrains the long-run coefficients to be identical, but allows the short- run coefficients and error variances to differ across groups The stationary case is considered as well as the case where the underlying regressors follow unit root processes, and for both cases the asymptotic distribution of the PMG estimator as T tends to infinity is derived, for a fixed N The authors also provide an empirical application to aggregate consumption functions across 24 OECD economies

Pooled estimation of long-run relationships in dynamic heterogeneous panels

A small quarterly macroeconometric model of the UK is estimated over the period 1965Q1 to 1995Q4 in eight core variables: domestic and foreign outputs, domestic and foreign prices (both measured relative to oil prices), the nominal effective exchange rate, nominal domestic and foreign interest rates and real money balances. The model is based on long-run relations from economic theory embodied in an otherwise unrestricted VAR framework. A main aim is to develop a core model with a trans-parent and theoretically coherent foundation. Tests of restrictions on the long-run relations of the model are presented. The dynamic properties of the model are illustrated through the use of persistence profiles and generalised impulse responses, which are invariant to the ordering of the variables in the VAR.

A Long-run Structural Macro-econometric Model of the UK

The paper considers international per capita output and its growth using a panel of data for 102 countries between 1960 and 1989. It sets out an explicitly stochastic Solow growth model and shows that this has quite different properties from the standard approach where the output equation is obtained by adding an error term to the linearized solution of a deterministic Solow model. It examines the econometric properties of estimates of beta convergence as traditionally defined in the literature and shows that all these estimates are subject to substantial biases. Our empirical estimates clearly reflect the nature and the magnitude of these biases as predicted by econometric theory. Steady state growth rates differ significantly across countries and once this heterogeneity is allowed for the estimates of beta are substantially higher than the consensus in the literature. But they are very imprecisely estimated and difficult to interpret. The paper also discusses the economic implications of these results for sigma convergence.

Growth and convergence: a multi-country empirical analysis of the solow growth model

Academic macroeconomics and the research department of central banks have come to be dominated by Dynamic, Stochastic, General Equilibrium (DSGE) models based on micro-foundations of optimising representative agents with rational expectations. We argue that the dominance of this particular sort of DSGE and the resistance of some in the profession to alternatives has become a straitjacket that restricts empirical and theoretical experimentation and inhibits innovation and that the profession should embrace a more flexible approach to macroeconometric modelling. We describe one possible approach.

M Pesaran

Papers

Exploring the International Linkages of the Euro Area: a Global VAR Analysis

Pooled estimation of long-run relationships in dynamic heterogeneous panels

A Long-run Structural Macro-econometric Model of the UK

Growth and convergence: a multi-country empirical analysis of the solow growth model

Beyond the DSGE Straitjacket