Profit margins and business cycles in the Brazilian industry: a panel data study

The paper investigates the relationship between profit margins and business cycle in the Brazilian industry during the 1992–1998 period, taking as reference a dynamic panel data model founded around a conjectural variation framework. The empirical results indicate procyclical behaviour of profit margins for the aggregate business cycle but is less clear in the case of sector-specific business cycle variables. Among the most robust results, one can highlight the roles of lagged profitability and import intensity and the negligible role of union density. Schmalensee in (American Economic Review 75, pp. 341–51) outlined three theoretical interpretations associated with the empirical model (classical, revisionist and managerial). Econometric tests on the related restrictions do not allow one to exclusively legitimate any of the three interpretations.     

Market share instability and stock price volatility during the industry life-cycle: the US automobile industry

Market share instability, during certain stages of the industry life-cycle, has become a stylized fact in the industrial organization literature. In the finance literature, volatility in the form of excess volatility, i.e. the much larger volatility of stock prices than dividends (although stock prices should in theory trace the present value of future dividends), has given rise to controversies regarding stock price determination (Campbell and Shiller, 1988; Shiller, 1989). Recent evolutionary models, both theoretical and empirical, have tied the presence of market share instability to industry specific variables, such as specific periods in the industry life-cycle and specific “technological regimes”. The object of the paper is to explore whether there is a relationship between market share instability and stock price volatility and to what degree this relationship is connected to the concept of the industry life-cycle, and hence to industry specific factors. To do so, we explore the relationship in one particular industry, the US automobile industry. Since neither life-cycle nor finance theories attack this problem directly, we use insights from both approaches to build hypotheses which guide the data analysis. The empirical results confirm many of these hypotheses, suggesting that the degree of excess volatility is indeed partly affected by industry specific factors.     

Convergence,technological interdependence and spatial externalities: a spatial dynamic panel data analysis

This study adopts a spatial dynamic panel data approach and spatial quasi-maximum likelihood to re-estimate the speed of growth convergence in 91 countries based on technological interdependence and spatial externalities. We perform a conditional Lagrange multiplier test for spatial error dependence and find some differences to previous studies. First, the switch from a cross-sectional to a dynamic panel data framework enables the estimated rate of conditional convergence to be higher, more accurate and more appropriate for realistic and theoretical expectations. Second, the spatial Durbin model (SDM) is a general form of simplified model that considers spatial error correlation, and its likelihood ratio test for the theoretical model of ‘learning by doing’ effect provides further evidence. Finally, statistical tests find that spatial correlation not only occurs in each variable, but also appears in the error term. Thus, the SDM does not exist in the assumptions associated with the spatial error, which are not necessarily correct.     

Renewable energy innovations in Europe: a dynamic panel data approach

We investigate the determinants of renewable energy R&D intensity and the impact of renewable energy innovations on firm performance, using several dynamic panel data models. We estimate these models using a large data set of European firms from 19 different countries, with some patenting activity in areas related to renewable energies during the 1987 to 2007 period. Our results confirm our priors on the determinants of the rapid development of renewable energy R&D intensity during the past decades. Additionally, we find evidence that renewable patent intensity has a significant dynamic impact on the stock market value of firms.     

Market discipline in the Brazilian banking industry: an analysis for the subordinated debt holders

Market discipline is a regulatory mechanism which has as its main task the punishment of bad risk management by financial institutions. Subordinated debt holders are considered by the literature as the most propitious private agent to discipline the financial institutions. The key to prove the existence of market discipline is to show the relationship between banks’ asset prices and its respective risks. The main objective of this article is an empirical analysis of the relation between credit risk (ratings and accounting information) and debentures return for the Brazilian case. The results denote a weak presence of market discipline in Brazil.     

The growth of university spin-offs: a dynamic panel data approach

Evidence suggests that a significant percentage of the university spin-offs (USOs) have a low growth capacity, putting in question the use of public funds to promote this kind of entrepreneurship. In addition, previous studies of the USOs’ growth have not dealt with the dynamic nature of firm growth, which might have led to questionable results. This paper analyses whether the university origin of a firm conditions its growth by applying a methodology which captures this dynamic nature of growth. Using a sample of 469 Spanish USOs and an equivalently matched group of 469 Spanish non-USOs over the period 2001–2010, we find that USOs have more growth than non-USOs, both in terms of sales and employment. In addition, the USOs’ growth is influenced by a set of determinants that differ from those of non-USOs. On the basis of the results, we propose some policies to foster the USOs.     

The missing link between innovation and performance in Brazilian firms: a panel data approach

This study aims to verify if there is a positive relationship between innovation and productivity and/or profit in Brazil using a recursive model in line with the Crépon, Duguet and Mairesse (CDM) model. Using a rich combination of three databases, this paper considers a sample of more than 10,000 Brazilian industrial firms and the period 2001–2008. Besides using R&D expenditure as a measure of innovation input, this study also tests the technical-scientific personnel stock as a more appropriate measure of innovative effort in emerging countries. This variable considers the tacit knowledge intrinsic to the worker and corrects a possible measurement error bias in the R&D expenditure variable. The empirical strategy uses a reduced form of the CDM model in a panel data structure to provide consistent estimates as it controls for selectivity, simultaneity and endogeneity due to unobserved firm effects. There are still few studies that apply the CDM model for panel data, especially regarding developing countries. The main results suggest that technical-scientific workers positively affect the firms’ probability to innovate while R&D expenditure has no effect. The results also highlight the absence of the effect of innovation on productivity and profit, suggesting a missing link between innovative efforts and Brazilian firms’ performance.     

Income and religion: a heterogeneous panel data analysis

A recent empirical literature has addressed the relationship between income and religion, but most of the studies are based on microdata. Macroeconomic analysis of the issue has largely ignored the potential heterogeneity between countries. Using retrospective data on church attendance rates for a panel of countries between 1925 and 1990, we apply heterogeneous panel data estimators and reveal that the effect of participation in religious activities on income per capita is mostly non-significant. This is consistent with some of the recent research that casts doubt onto the influence of religion on income, once causality is taken into account.     

Financial openness and capital mobility: a dynamic panel analysis

Does unrestricted control on the movement of capital increase capital mobility? Theoretically, the answer is yes. This paper uses the Feldstein–Horioka savings–investment methodology to examine the impact of financial openness on the degree of capital mobility in 104 countries. Our estimates suggest that financial openness has increased capital mobility in developing countries, while its effect is statistically insignificant in OECD countries. This also implies that a developing country with more financial openness can have more access to external capital markets for borrowings. Foreign aid also appears to supplement domestic savings for investment in developing countries. In line with the previous findings, our study also confirms that capital is more mobile for developing countries.     

Tourism and trade in OECD countries. A dynamic heterogeneous panel data analysis

This article studies the empirical link between international tourism and trade. We apply dynamic heterogeneous panel data techniques to analyse both long and short-run relationship for the case study of OECD countries. This link is studied by estimating the cointegration vector and analysing the short causality between variables. The analysis recognises that inbound tourism can promote international trade and also that international flow of goods requires and may encourage tourist arrivals and departures. The statistical significance of this link supports the presence of business opportunities due to the potential complementary relationship between tourism and trade. The results suggest a short-run nexus between tourism and trade, and that these variables are cointegrated.     

Determinants of international tourism: a three-dimensional panel data analysis

International tourism is a fast growing industry generating half a trillion dollars in annual revenues and accounting for almost 10%?of total international trade, and almost half of total trade in services. Yet, it has so far failed to receive the attention it deserves from mainstream economics. This paper attempts to provide an initial understanding of the determinants of international tourism. This paper claims that international tourism, as other forms of trade in services, is driven by unique factors of production, and may be better dealt with in a single industry study rather than in a general equilibrium trade model. In order to understand these determinants the world is viewed as a market of differentiated products, and a discrete choice estimation technique is applied to a large three-dimensional data set of tourist flows. It is shown that a relatively simple estimation technique, combined with a rich data set, can deliver reasonable substitution patterns. It is found, among other things, that political risk is very important for tourism, and that exchange rates matter mainly for tourism to developed countries. These have exchange rate elasticity of about one.     

Technological progress and scientific indicators: a panel data analysis

Total factor productivity (TFP) is generally interpreted to be a proxy for technological advancement. In this paper, we use stochastic frontier analysis to decompose the growth in TFP into three components: technological progress, scale effect and change in technical efficiency. Then, we conduct a comprehensive panel data analysis using the technological progress component of the TFP growth and several scientific and technological indicators using data from 160 countries over the period from 1960 to 2009. Our results generally show that the technological progress component of the TFP growth properly reflects certain dimensions of actual scientific and technological progress. However, we also find that this result is somewhat sensitive to different econometric specifications and assumptions.     

Entrepreneurship and income inequality: a spatial panel data analysis

The main objective of this paper is to empirically analyze the relationship between entrepreneurship and income inequality. We use a spatial panel data analysis for both 33 high-income countries and 39 middle- and low-income countries over a period of 11 years. Estimation results and rigorous diagnostic analysis suggest that: (i) there is a strong support for the existence of an inverted U-shaped relationship between entrepreneurship and income inequality espoused by the Kuznets Curve hypothesis; (ii) the relationship between entrepreneurship and income inequality is negatively moderated by country’s level of economic development; (iii) regardless of income inequality levels, entrepreneurship has a non-linear relationship with income per capita; (iv) gross domestic expenditure on research and development exhibits significant negative impacts on entrepreneurship; (v) significant mixed effects on the likelihood of entrepreneurial activity are observed with governance, globalization, population growth rate, and competitiveness variables; (vi) there are significant mixed feedback effects on entrepreneurship; and (vii) there are statistically significant, positive as well as negative spatial spillovers to country-level entrepreneurial activity.     

The macroeconomy and microfinance outreach: a panel data analysis

This study examines the effects of macroeconomic and institutional factors on microfinance institution (MFI) outreach. To capture the performance of the macroeconomy, we include proxies for institutional quality, economic growth, FDI inflow, unemployment rate, inflation and the prevalence of wage-earning jobs. Further, we examine effects on outreach along the dimensions of outreach depth and outreach breadth. Using data on 1526 MFIs from 99 countries over the period 2000 to 2015, our results suggest that environments characterised by high levels of economic performance and good institutions tend to hinder outreach performance. These results suggest that MFIs depend on a poor economy to thrive given the informal nature of microfinance.     

On IV,GMM and ML in a dynamic panel data model

For the basic dynamic panel data model we give an expression for the optimal instrumental variable (IV) estimator and show that the generalized method of moments (GMM) does not add to the asymptotic efficiency. It is recommended to exploit the full set of orthogonality conditions as given by Ahn and Schmidt.     

Understanding wage determination in a multi-level bargaining system: a panel data analysis

This article presents an estimation of the elasticity of actual wages to industry-level collective bargaining thereby quantifying empirically the role of industry-level bargaining on wage determination. For this purpose, we use a unique employer–employee panel dataset covering the entire Belgian employment population over 9 years (1998–2006). Like several other European countries, e.g. Germany, France, Italy and the Netherlands, Belgium has a relatively centralised wage bargaining system, with the industry level playing the most important role. Regression results confirm that wage increases collectively decided at the industry level are, on average, fully passed on to individual wages. In addition to industry-level bargaining, we are interested in the supplementary wage increases granted at the firm level, referred to as wage drift or wage cushion in the literature. Our estimates show that wage drift is affected by company size, by the economic performance of the industry and to a much lesser extent by labour market tensions as measured by the local unemployment rate. Interestingly, our results show that industry-level bargaining also takes most of these features into account.     

Deep habits in consumption: a spatial panel analysis using scanner data

Using scanner data from a large European retailer, this paper empirically assesses deep habit formation in consumption. Deep habit formation constitutes a possible source of price stickiness and helps to mimic procyclical labour and real wage dynamics that are present in macrodata. To gauge the existence and the extent of deep habits in consumption, we estimate a dynamic time–space simultaneous model for consumption expenditure at different levels of product aggregation. This spatial panel model enables us to test for both internal and external deep habit formation at the same time. The former captures inertia or persistence in consumption and is included in the empirical specification as a time lag. The latter captures preference interdependence across households and is captured by a spatial lag. Our results show mixed evidence with respect to internal habit formation, whereas the external habit effect is almost always positive and significant.     

Output growth and investment dynamics in Finland: a panel data analysis

This study analyzes the relationship between output growth and investment in a panel of 20 regions of Finland over the period 1975–2007. This regional study uses Granger non-causality and error-correction models. The most important finding of this study is a unidirectional causality which runs from investment to output growth. The study also verifies the existence of a positive association between growth and investment for the panel of 20 regions of Finland. These findings reconcile with the capital fundamentalists.     

Spatial analysis of municipal water demand: a panel data approach

While the municipal water demand literature is well developed, one area that is understudied is the impact of spatial effects. After controlling for factors shown to impact demand, this study applies spatial econometric methods via a spatial weights matrix to a panel municipal water consumption data set. While diagnostics suggest the presence of spatial lag and spatial error, thus indicating the potential usefulness of spatial empirical methods, several important pitfalls must be acknowledged. First, the application of spatial weights in a panel setting is computationally intensive, especially when the number of time periods or observations is large, and perhaps necessitates aggregation. Second, because most users in a municipality are likely to be subject to similar utility action, climate, etc., a spatial lag signal may be spurious. Third, because premises served by the utility may enter or exit the data set through time, the requirement of balanced panels requires careful consideration. Fourth, if the option to use premises-level (or similar) data or aggregated data is available, it is typically advisable to use premises-level data despite the possible presence of spatial effects.