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This chapter revisits the Hausman (1978) test for panel data. It emphasizes that it is a general specification test and that rejection of the null signals misspecification and is not an endorsement of the fixed effects estimator as is done in practice. Non-rejection of the null provides support for the random effects estimator which is efficient under the null. The chapter offers practical tips on what to do in case the null is rejected including checking for endogeneity of the regressors, misspecified dynamics, and applying a nonparametric Hausman test, see Amini, Delgado, Henderson, and Parmeter (2012, chapter 16). Alternatively, for the fixed effects die hard, the chapter suggests testing the fixed effects restrictions before adopting this estimator. The chapter also recommends a pretest estimator that is based on an additional Hausman test based on the difference between the Hausman and Taylor estimator and the fixed effects estimator.

Purpose – This chapter considers a Hausman and Taylor (1981) panel data model that exhibits a Cliff and Ord (1973) spatial error structure.

Methodology/approach – We analyze the small sample properties of a generalized moments estimation approach for that model. This spatial Hausman–Taylor estimator allows for endogeneity of the time-varying and time-invariant variables with the individual effects. For this model, the spatial fixed effects estimator is known to be consistent, but its disadvantage is that it wipes out the effects of time-invariant variables which are important for most empirical studies.

Findings – Monte Carlo results show that the spatial Hausman–Taylor estimator performs well in small samples.

This study aims to empirically explore whether there is causality and in which direction, i.e. whether financial development generates economic growth or whether financial development merely follows economic growth in transition European countries, including Russian Federation and Turkey, during 1998-2015.

The study uses different techniques such as pooled OLS, fixed and random effects and the Hausman–Taylor model with instrumental variables.

The regression results show a positive relationship between financial development indicators and real GDP per capita growth, thus supporting the hypothesis that finance leads economic growth. The result also shows that financial crisis has a negative effect on real GDP per capita growth. Furthermore, these findings show that government spending and inflation have a negative impact on real GDP per capita growth. The study also shows that financial development plays growth-supporting role in real GDP per capita growth in 20 European countries in transition, including Russian Federation and Turkey.

As financial development generates real GDP per capita growth, on the basis of the results of the study, a course of action that involves institutional improvement and incentivizing competition in the financial sector is recommended to the Central Banks’ policymakers in transition economies. These will in turn lead to higher real GDP per capita growth.

The study is original in nature and makes effort to promote financial development in transition European countries, including Russian Federation and Turkey. The findings of this study will be of value to Central Banks and other policymakers.

This chapter suggests a robust Hausman and Taylor (1981), hereafter HT, estimator that deals with the possible presence of outliers. This entails two modifications of the classical HT estimator. The first modification uses the Bramati and Croux (2007) robust Within MS estimator instead of the Within estimator in the first stage of the HT estimator. The second modification uses the robust Wagenvoort and Waldmann (2002) two-stage generalized MS estimator instead of the 2SLS estimator in the second step of the HT estimator. Monte Carlo simulations show that, in the presence of vertical outliers or bad leverage points, the robust HT estimator yields large gains in MSE as compared to its classical Hausman–Taylor counterpart. We illustrate this robust version of the HT estimator using an empirical application.

This paper aims to estimate the impact of job search on the internet on the probability of re‐employment and the duration of unemployment spells.

The study uses national panel datasets from Germany (SOEP 2003‐2007) and South Korea (KLIPS 1996‐2006) to estimate probit and Hausman‐Taylor IV models of the impact of job search on the internet on the probability of re‐employment. The study also explores duration analysis with the aim of estimating the impact of internet job search on the duration of unemployment.

In Germany and South Korea job seekers who used the internet had a 7.1 and 12.7 percentage point higher probability, respectively, of being re‐employed in the next 12 months. Furthermore, job seekers who used the internet had a shorter duration of unemployment in both Germany and South Korea.

Over the past decade, internet penetration rates and use of the internet in job search have risen sharply across the world. The internet has significantly changed the job application process and improved the channels of communication between employers and job seekers. The findings of the research indicate that the internet is beneficial and should be a part of job search efforts.

The contribution of this study is twofold. It is the first study to use panel datasets to analyze the link between internet use and job search outcomes. Therefore, the results are robust to unobserved heterogeneity problems. The study also addresses the issue of endogeneity of job search on the internet by using the Hausman‐Taylor IV model.

The purpose of this paper is to empirically examine the macroeconomic determinants of Port wine exports, taking into account the diversity and various quality levels associated with this product.

Port wine is a fortified wine only produced in Portugal. In the period 2006-2014, an extended gravity model is applied to data on the exports of the top 20 importing countries, accounting for 94 per cent of total exports. The authors base their empirical strategy on the Hausman–Taylor estimator (1971), overcoming endogeneity and accounting for time invariant variables. They estimate the impact of several factors on the total trade of Port wine, namely: gross domestic product (GDP), GDP per capita, tariffs, exchange rates, distance from original supplier, mutual language familiarity, landlockedness, wine consumption per capita and presence of Portuguese emigrants, all measured in volume and value terms, and for each of the four categories (Standard, High Standard, Vintage and Aged).

The findings show that the quantity and value of total Port wine exports are positively determined by overall GDP per capita, the presence of a Portuguese emigrant community (which implies that to some degree a common language and culture are shared), while exports are negatively influenced by landlockedness. In contrast to the traditional gravity model, distance from the source of supply does not appear to be a significant determinant, a fact explained by the specific and singular nature of Port wine and by the long tradition of this product in international markets. In addition, the results revealed specific determinants for specific product categories – such as GDP for aged Port and wine consumption per capita for high standard, vintage and aged Port, suggesting that Portugal needs to increase its exports of high-quality Port wine to markets that exhibit a tendency towards increased wine consumption per capita and are coming to be considered large and fast-growing economies.

This paper extends the literature, by respecifying the typical gravity model for aggregate goods to permit the analysis of wine exports. There has been relatively little application of this model to assess the determinants of the wine trade, and when it has been used, generally it has been in studies focusing on aggregate wine trade between countries. This paper seeks to fill this gap by focusing on the determinants of exports of a specific wine – Port wine, which is an internationally recognised product, with a clear internal product differentiation according to distinct quality levels – and in this regard provides new insights into the international patterns of trade in wine.

Unlike the traditional growth model of emerging markets after economic liberalization, India’s inward foreign direct investment (FDI) surged paralleling its strong economic growth in the 2000s, despite the failure to establish a strong secondary sector. This creates an opportunity to deepen the conceptual and contextual understanding of the pivotal mechanisms that impel foreign multinational enterprises to invest into India and provides a natural setting to better understand the nature of its institutional, political and economic environment.

The authors develop a theory contextualized to Indian inward FDI patterns for the 2000–2017 period. The theoretical framework expands upon received investment motives, with explicit consideration given to the idiosyncrasies of developments in India’s recent macro and socioeconomic environment. The authors test the hypotheses using panel data from 134 countries that invested in India, using a Hausman–Taylor estimation.

The authors find that India’s transition toward a knowledge economy attracts asset augmenting rather than asset exploiting FDI. Investors appear to target long-term investments by gaining access to India’s digital capabilities, R&D, and growing talent base with a high degree of specialization within analytics, biotechnology, engineering, or pharmaceuticals. Foreign investors do not seem to be notably deterred by infrastructural challenges nor by legal and regulatory restrictions.

By providing a new perspective on India’s atheoretical economic development and FDI environment, this study offers a distinct point of comparison with regard to established hypotheses within the extant literature on FDI into emerging markets. Rethinking contemporary investment motive theory by introducing an adapted conceptual framework provides further opportunity to inform the understanding of firm strategies in similar environments.

Purpose: In reality, financial decisions are made under conditions of asymmetric information that results in either favorable or adverse selection. As far as financial decisions affect growth of the firm, the latter must also be affected by either favorable or adverse selection. Therefore, the core objective of this chapter is to examine the determinants of each financial decision and the effects on growth of the firm under conditions of information asymmetry.

Design/Methodology/Approach: This chapter uses data for the non-financial firms listed in S&P 500. The data cover quarterly periods from 1989 to 2014. The statistical tests include linearity, fixed, and random effects and normality. The generalized method of moments estimation method is employed in order to examine the relative significance and contribution of each financial decision on growth of the firm, respectively. Standard and proposed proxies of information asymmetry are discussed.

Findings: The results conclude that there is a variation in the impact of financial variables on growth of the firm at high and low levels of information asymmetry especially regarding investment and financing decisions. A similar picture emerges in the cases of firm size and industry effects. In addition, corporate dividen d policy has a similar effect on firm growth across all asymmetric levels. These findings prove that information asymmetry plays a vital role in the relationship between corporate financial decisions and growth of the firm. Finally, the results contribute to the vast literature on the estimation of information asymmetry by demonstrating that the classical and standard proxies for information asymmetry are not consistent in terms of the ability to differentiate between favorable or adverse selection (which corresponds to low and high level of information asymmetry).

Originality/Value: This chapter contributes to the related literature in two ways. First, this chapter offers updated empirical evidence on the way that financing, investment, and dividends decisions are made under conditions of favorable and adverse selection. Other related studies deal with each decision separately. Second, the study offers new proxies for measuring information asymmetry in order to reach robust estimates of the effects of financial decisions on growth of the firm under conditions of agency problems.

The internal factors that influence the decision to change dividend growth rates include two competing models: the earnings and free cash flow models. As far as each of the components of each model is considered, the informative and efficient dividend payout decisions require that managers have to focus on the significant component(s) only. This study examines the cointegration, significance, and explanatory power of those components empirically. The expected outcomes serve two objectives. First, on an academic level, it is interesting to examine the extent to which payout practices meet the premises of the earnings and free cash flow models. The latter considers dividends and financing decisions as two faces of the same coin. Second, on a professional level, the outcomes help focus the management’s efforts on the activities that can be performed when considering a change in dividend growth rates.

This study uses data for the firms listed in two indexes: Dow Jones Industrial Average (DJIA30) and NASDAQ100. The data cover quarterly periods from 30 June 1989 to 31 March 2011. The methodology includes (a) cointegration analysis in order to test for model specification and (b) classical regression in order to examine the explanatory power of the components of earnings and free cash flow models.

The results conclude that: (a) Dividends growth rates are cointegrated with the two models significantly; (b) Dividend growth rates are significantly and positively associated with growth in sales and cost of goods sold only. Accordingly, these are the two activities that firms’ management need to focus on when considering a decision to change dividend growth rates, (c) The components of the earnings and free cash flow models explain very little of the variations in dividends growth rates. The results are to be considered a call for further research on the external (market-level) determinants that explain the variations in dividends growth rates. Forthcoming research must separate the effects of firm-level and market-level in order to reach clear judgments on the determinants of dividends growth rates.

This study contributes to the related literature in terms of offering updated robust empirical evidence that the decision to change dividend growth rate is discretionary to a large extent. That is, dividend decisions do not match the propositions of the earnings and free cash flow models entirely. In addition, the results offer solid evidence that financing trends in the period 1989–2011 showed heavy dependence on debt financing compared to other related studies that showed heavy dependence on equity financing during the previous period 1974–1984.