The Singapore Economic Review

We study the effects of free trade areas on bilateral trade flows. We review and extend the previous empirical literature by embarking on the modelling of unobserved heterogeneity. We apply our preferred model to the case of the Asean Free Trade Area (AFTA). The estimation results suggest that there has been a positive effect of AFTA. This empirical finding is contrary to earlier estimation results, which are typically not so positive about AFTA. It is our impression that these earlier estimates on AFTA are confounded with the effects of unobserved determinants of trade.

Investment Climate surveys (ICs) are a recent instrument used by the World Bank to identify key obstacles to country competitiveness and to guide policy reforms and government interventions in developing countries. In this paper, panel data from four ICs of four South East Asian (SEA) countries namely, Indonesia, Malaysia, The Philippines, and Thailand, are pooled to estimate total factor productivity (TFP) and allocative efficiency aspects of firms in each country, using variants of the Olley and Pakes (1996) productivity decomposition. Several economic performance results are disaggregated to obtain country-specific evaluation of the IC impacts. To establish priorities for policy reforms, the corresponding key IC results are organized in five categories: infrastructures, red tape, corruption and crime, finance and corporate governance, quality, innovation and labor skills, and other control variables.

A long-standing issue in industrial economics is the understanding of the relative prevalence of labor-managed firms (LMFs) and capitalist firms across industries. In proportionate terms, LMF entry tends to be highly concentrated in particular industries. We provide empirical evidence on this by modeling the proportions of industry entrants that are LMFs, using a panel of UK manufacturing industries. Random effects proportions models indicate the role and importance of risk and capital requirements as potential deterrents to LMF entry.

Intangible assets like human capital and organization capital have driven the success of India's software industry. This article analyzes the impact of intangible assets on the market value of Indian software firms using a dynamic panel data model. Measures of tangible and intangible assets are constructed using firm-level panel data. The estimation technique uses system generalized method of moments (GMM) and minimum distance estimation (MDE). This methodology accounts for unobserved firm heterogeneity, endogenous explanatory variables and persistent variables. The results conclusively show that intangible assets have a significant impact on market values of Indian software firms.

Transition from economic theory to a testable form of model invariably involves the use of certain "simplifying assumptions." If, however, these are not valid, misspecified models result. This article considers estimation of the dynamic linear panel data model, which often forms the basis of testable economic hypotheses. The estimators of such a model are frequently similarly based on certain assumptions which appear to be often untenable in practice. Here, the performance of these estimators is analyzed in scenarios where the theoretically required conditions are not met. Specifically, we consider three such instances of serial correlation of the idiosyncratic disturbance terms; correlation of the idiosyncratic disturbance terms and explanatory variables; and, finally, cross-sectional dependence (as a robustness check to these findings, we also consider correlations between observed and unobserved heterogeneity terms). The major findings are that the limited tests readily available tend to have poor power properties and that estimators' performance varies greatly across scenarios. In such a wide array of experiments, it is difficult to pick-out just one "winner." However, a robust estimator across all experiments and parameter settings was a variant of the Wansbeek–Bekker estimator. This is a significant finding, as this estimator is infrequently used in practice. When the experiments are extended to include correlations between observed and unobserved heterogeneity terms, one might also consider, for across-the-board performance, the Blundell and Bond estimator.

This article applies the panel stationarity test with a break proposed by Hadri and Rao (2008) to examine whether 14 macroeconomic variables of OECD countries can be best represented as random walk or stationary fluctuations around a deterministic trend. In contrast to previous studies, based essentially on visual inspection of the break type or just applying the most general break model, we use a model selection procedure based on BIC. We do this for each time series so that heterogeneous break models are allowed for in the panel. Our results suggest, overwhelmingly, that if we account for a structural break, cross-sectional dependence and choose the break models to be congruent with the data, then the null of stationarity cannot be rejected for all the 14 macroeconomic variables examined in this article. This is in sharp contrast with the results obtained by Hurlin (2004), using the same data but a different methodology.

A relatively new type of panel data analysis is becoming more and more topical in the applied econometrics literature as auction mechanisms are being explored in more depth. The typical data utilized in such studies involves repeated measures of auction outcomes, where the variable of interest involves order statistics from the sample of bids from many bids on completed auctions for a particular commodity. This article presents structural estimates of bidding behavior in eBay computer monitor auctions. We exploit characteristics of such repeated measures to analyze the efficiency of private value auctions for a relatively homogeneous good, computer monitors sold on eBay. We discuss how outcomes of the auction mechanism can be analyzed and their equilibrium outcomes assessed and evaluate the consumer surplus that is generated from such auctions. Particular attention is given to the collection of the eBay data from data recovery protocols that monitor in real time and in relative detail, characteristics of a particular auction with heterogeneity controls for different types of monitors and for different reputation effects of the auctioneer. Among other findings, our results point to a rejection of the use of Jump Bidding (Avery, 1998) or "Snipe or War" bidding (Roth and Ockenfels, 2002). We also find that longer auctions only have a small effect on price and experienced auctioneers respond to this incentive.

Social capital is widely regarded to constitute an important indicator for the economic performance of a society. This paper analyzes the impact of various socio-demographic characteristics on social capital. Proxy variables for social capital are obtained from a comprehensive principal components analysis exercise using survey data from the British Household Panel Survey (BHPS). The BHPS provides information on social and economic change at the individual and household levels in Britain and the UK with an annual survey of ca. 10,000 individuals from ca. 5,000 households. Based on the 13th wave of this database, we investigate the impact of exogenous qualities, individually acquired characteristics, and of the social environment using a spatial auto-regression framework. The results show that the formation of social capital can be modeled to a very high degree of statistical accuracy. The structural effect from the households contributes substantially to the social capital level of each household member. Thus, the social capital formation can be based equally on individual measures (such as education) and social contagion processes.