Panel data analysis of multi-factor capital asset pricing models

In this article, we propose MFCAPM panel models with fixed effects and test theories associated with risk exposures and anomalies postulated by Fama and French, and we assess their out-of-sample predictive performances. Based on the portfolios formed by French, we construct 10 panel models, each consisting of 10 portfolios grouped by size deciles, and another 10 panels by value deciles. In the presence of cross-section dependence, the MFCAPM panel model is estimated by the feasible generalized least squares (FGLS) method for the sample period 1963(1)-2018(9). The results show that the market, firm-size and value risk exposures are significant and robust across three-, five- and six-factor panel models. Significant time-fixed effects indicate that there are several portfolios resilient to dot.com bubble peak in 2000, while some others resilient to GFC in 2007. We estimate the models for the in-sample period 1963(1)–1999(12) and generate the out-of-sample portfolio returns for the period 2000(1)–2018(9). We find that portfolio returns forecasts generated by the six-factor panel model are superior to other MFCAPM panel models, mostly due to the momentum factor (investor behaviour) explaining large return variations and volatility exposures. The findings have implications for investors, security traders and portfolio risk managers.     

Segmented stochastic convergence across the G-7 countries

This paper analyzes the stochastic convergence in per capita income levels among the current G-7 over the period 1900–89. We show that, in the presence of possible structural breaks, the strong condition of stationary pair-wise differences between per capita GDP holds in more cases than previously supposed. However, convergence occurs more frequently in the first part of the time sample than in the second one. First version received: June 1999 / Final version accepted: Feb. 2000     

Price convergence across regions in India

The paper attempts to examine whether there is price convergence across various regions in India. Using panel unit root tests that are robust to cross-sectional dependence, it is found that relative price levels among various regions in India are mean-reverting. Further, we decompose each series into a set of common factors and idiosyncratic components. The decomposition enables us to test stationarity and estimate half-lives of the common factors and the idiosyncratic components separately. Both these components are found to be stationary. Idiosyncratic price shocks, however, are found to be more persistent as compared to the common factor. Results also indicate that transportation cost proxied by distance can explain a part of the variation in prices between two locations in India. The authors would like to thank Dibyendu Bhaumik for arranging the data for this study. Views expresed in the paper are personal and do not reflect the views of the organizations.     

Estimating most productive scale size with stochastic data in data envelopment analysis

This article estimates most productive scale size in stochastic data envelopment analysis (DEA). Jahanshahloo and Khodabakhshi [Jahanshahloo, G.R. and Khodabakhshi, M., Using input–output orientation model for determining most productive scale size in DEA. Applied Mathematics and Computation 2003, 146(2–3), 849–855.] studied most productive scale size in classic data envelopment analysis. The classic data envelopment analysis requires that the values for all inputs and outputs be known exactly. However, this assumption may not be true, because data in many real applications cannot be precisely measured. One of the important methods to deal with imprecise data is considering stochastic data in DEA. Therefore, this research studies most productive scale size with considering stochastic data in DEA. To that end, input–output orientation model introduced in Jahanshahloo and Khodabakhshi [Jahanshahloo, G.R. and Khodabakhshi, M., Using input–output orientation model for determining most productive scale size in DEA. Applied Mathematics and Computation 2003, 146(2–3), 849–855.] is extended in stochastic data envelopment analysis. To solve the stochastic model, a deterministic equivalent is obtained. Although the deterministic equivalent is non-linear, it can be converted to a quadratic program. Furthermore, data of software companies is used to apply the proposed approach. Performance of software companies are evaluated based on their scale sizes in classic and stochastic data envelopment analysis.     

Purchasing power parity across Mexican cities: a panel data analysis

This article presents three different unit root tests for panel data, the main objective is to find the level of internal integration market through the purchasing power parity (PPP) evidence, based in the Balassa–Samuelson approach. Thus, eight kinds of markets, as tradable and nontradable goods for 16 main Mexican cities during a 21 year period have been contrasted. While two tests showed the PPP validity for seven markets, the other rejected it. The results obtained moreover feed the present controversy about which test is most appropriate to test the PPP, as soon as it is highlighted new elements emerge to explain the half-life analysis.     

Testing stochastic income convergence in seasonal heterogeneous panels

In this paper we introduce a seasonal version of the Solow–Swan growth model and acquire an empirical income convergence equation. We take this equation as a basis to investigate whether income convergence exists in an OECD sample. To do this, we propose the test statistics under various asymptotic properties for some of the seasonal frequencies in the context of nonstationary heterogeneous panels. Critical values and moments of our statistics are generated and their finite sample performances are examined via Monte Carlo simulations.     

Almost sure convergence to zero in stochastic growth models

This paper considers the resource constraint commonly used in stochastic one-sector growth models. Shocks are not required to be i.i.d. It is shown that any feasible path converges to zero exponentially fast almost surely under a certain condition. In the case of multiplicative shocks, the condition means that the shocks are sufficiently volatile. Convergence is faster the larger their volatility, and the smaller the maximum average product of capital.I would like to thank Santanu Roy, John Stachurski, Lars J. Olson, and an anonymous referee for helpful comments and suggestions. The general result in section 2 owes much to the referee’s comments on an earlier version of this paper. Financial support from the 21 Century COE Program at GSE and RIEB, Kobe University is gratefully acknowledged.     

Total factor productivity and the convergence hypothesis in the Italian regions

This article is aimed at testing the catching up hypothesis for the Italian regions. The use of Malmquist productivity indices allows to decompose productivity growth into technological progress and technical efficiency change, interpreted respectively as innovation and catching up measurements. The analysis leads to a conclusion that regional economies diverge at a decreasing rate.     

Testing convergence of European regions: A semiparametric approach

We provide a reappraisal of income convergence across European regions over the last two decades by using a semiparametric partially linear model to approximate the relationship between the average growth rate of GDP per capita and the initial GDP per capita. Estimation results point out both country heterogeneity and non-linearity in the convergence process. The findings suggest that low income regions, in particular those from new adhesion countries, diverge while medium income regions converge and that there is no evidence of convergence for high income regions.     

Panel data inference under spatial dependence

This paper focuses on inference based on the standard panel data estimators of a one-way error component regression model when the true specification is a spatial error component model. Among the estimators considered, are pooled OLS, random and fixed effects, maximum likelihood under normality, etc. The spatial effects capture the cross-section dependence, and the usual panel data estimators ignore this dependence. Two popular forms of spatial autocorrelation are considered, namely, spatial autoregressive random effects (SAR-RE) and spatial moving average random effects (SMA-RE). We show that when the spatial coefficients are large, test of hypothesis based on the standard panel data estimators that ignore spatial dependence can lead to misleading inference.     

Efficiency and technical progress: sources of convergence in the Spanish regions

The paper analyses the contribution of efficiency as a mechanism of labour productivity convergence, taking as the unit of analysis the Spanish regions in the period 1964–1993. Using the stochastic frontier approach, a translogarithmic production function is estimated for the different sectors of the Spanish regional economy, demonstrating on this basis the existence of substantial differences in efficiency between sectors as well as between regions. With regard to convergence, the results obtained indicate that at aggregate level the convergence observed in labour productivity is explained by the faster growth of the capital-labour ratio of the initially poorer regions and the contribution of technical change and the efficiency, hence by the convergence of TFP. However, the information by sectors shows different results. Thus, on the one hand, the importance of the convergence in production per employee is seen in all sectors except agriculture and, on the other it is observed that technical change is a factor of convergence in all sectors but construction, and, qualitatively, the contribution of technical change is greater than the contribution of efficiency. By sectors, technical change contributed significantly to labour productivity convergence in agriculture, but the faster growth of the capital-labour ratio of the rich regions acted as a mechanism of divergence, completely counteracting the technological catching-up effect. It is further concluded that, as well as the contribution of the accumulation of factors, the positive evolution of efficiency in the poorest regions favoured convergence in the construction and industry sectors, whereas technical progress was decisive in industry and the services sectors.     

A pair-wise approach to output convergence between European regions

We apply the Pesaran (2007) pair-wise approach of convergence to the per capita outputs of 195 European regions for the period 1980-2006. Pesaran's approach is based on the computation of the percentage ratio of output gaps which fulfil a given convergence criterion. A high ratio will be interpreted in favour of convergence. In a first step, we define stochastic convergence between two regions as level stationarity of their output gap. Deviations from its equilibrium value will only have a temporary effect. Results from several usual unit root or stationarity tests show us that the percentage ratio of level stationary output gaps is low, which stands against this definition of convergence. However, this convergence criterion excludes the possibility of changes in output gap equilibrium value or catching up between regions. To fit these cases, we combine the pair-wise approach with unit root or stationarity tests with structural breaks. Structural breaks are modelled by dummies (Zivot and Andrews, 1992; Kurozumi,2002) or as smooth structural breaks (Christopoulos and León-Ledesma, 2009). Overall results are not changed as convergence is not accepted more often. Finally, we consider the autocorrelation function approach of Caggiano and Leonida (2009). Autocorrelations and their confidence intervals are estimated for each output gap. Convergence between two regions is accepted if their per capita output gap autocorrelations become nonsignificantly different from zero after some lag. Results show that a high percentage of regions satisfy this convergence criterion. Contrary to the conclusions which could be made from previous results, shocks to output gaps seem to disappear as time passes.     

An economic efficiency study on different regions of Ghana via Slack-based data envelopment analysis and regression analysis

In this article, we evaluate the efficiency of the 10 different regions of Ghana using slack-based data envelopment analysis, a nonparametric linear programming technique. Furthermore, we analyse the variable effects on the efficiency of the regions by various regression models using bootstrap sampling technique. The data come from the 1991/1992 and 1998/1999 Ghana Living Standards Survey. Our results show that wealth is not strongly related to efficiency. For example, the study indicates that the Brong–Ahafo region is the most efficient region but not the most wealthy in Ghana. Generally, urban regions are not found to be among the most efficient regions due to the high expenditures. The regression analysis shows that female heads of household have an overall positive effect on efficiency. In addition, any form of education obtained is also found to have a significant positive effect on efficiency.     

Fractional cointegration analysis of EU convergence

Traditional cointegration tests do not provide strong evidence of convergence between EU countries. In this study, fractional cointegration analysis is used to test for convergence between EU members. Fractional cointegration between inflation and between long-term interest rates is found. The results indicate that there is nominal convergence, but that the equilibrium errors display long memory. Fractional cointegration analysis gives no evidence of real convergence in output.     

Inequality and convergence in Europe's regions: reconsidering European regional policies

In this paper we take a critical look at current European regional policies. First, we document the motivation for such policies, that is, the large income disparities across the regions of the EU15. Large disparities are certainly present. Second, we illustrate the various instruments adopted and discuss their underpinnings in established economic theories. Next, we look at available data, searching for three kinds of evidence: (1) if disparities are either growing or decreasing, we conclude they are neither; (2) which are the major factors explaining such disparities and, in particular, if they are the factors predicted by the economic models adopted by the Commission to justify current policies, we conclude this is most certainly not the case; (3) if there are clear signs that EU policies, as opposed to other social and economic factors, are actually reducing such disparities, we cannot find any clear sign of such desired impact. Our conclusion is that regional and structural policies serve mostly a redistributional purpose, motivated by the nature of the political equilibria upon which the European Union is built. They have little relationship with fostering economic growth. This casts a serious doubt on their social value and, furthermore, strongly questions extending such policies to future members of the European Union. A successful EU enlargement, in our view, calls for an immediate and drastic revision of regional economic policies.
— Michele Boldrin and Fabio Canova     

Labor market integration policies and the convergence of regions: the role of skills and technology diffusion

We study the role of different labor market integration policies on economic performance and convergence of two distinct regions in an agent-based model. Production is characterized by a complementarity between the quality of the capital stock and the specific skills of workers using the capital stock. Hence, productivity changes in a region are influenced both by the investment of local firms in high quality capital goods and by the evolution of the specific skill distribution of workers employed in the region. We show that various labor market integration policies yield, via differing regional worker flows, to distinct regional distributions of specific skills. Through this mechanism, relative regional prices are affected, determining the shares that the regions can capture from overall consumption good demand. There occurs a trade-off between aggregate output and convergence of regions with closed labor markets resulting in relatively high convergence but low output, and more integrated labor markets yielding higher output but lower convergence. Furthermore, results differ substantially in several respects as distinct labor market opening policies are applied.