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Economists (should) care about regions! On the one hand this is true because macroeconomic shocks have vastly different effects across regions. The pressing topics of robotization
and artificial intelligence, Brexit, or U.S. tariffs will affect Würzburg differently than Berlin,
implying varying interests among its population, firms and politicians. On the other hand,
shocks in individual regions, such as inventions, bankruptcies or the attraction of a major
plant can, through trade and input-output linkages, magnify to aggregate effects of macroe-
conomic importance. Yet, regional heterogeneities in Germany and the complicated network
of linkages that connect regions are still not well documented nor understood. A fact that
is especially true for local labor markets that are of core interest to regional policy makers
and that also feature substantial heterogeneity.
This thesis provides a thorough quantification of such heterogeneities and an in-depth analysis of the sources and mechanisms that drive these differences.
The present thesis analyzes whether and - if so - under which conditions mergers result in merger-specific efficiency gains. The analysis concentrates on manufacturing firms in Europe that participate in horizontal mergers as either buyer or target in the years 2005 to 2014.
The result of the present study is that mergers are idiosyncratic processes. Thus, the possibilities to define general conditions that predict merger-specific efficiency gains are limited.
However, the results of the present study indicate that efficiency gains are possible as a direct consequence of a merger. Efficiency changes can be measured by a Total Factor Productivity (TFP) approach. Significant merger-specific efficiency gains are more likely for targets than for buyers. Moreover, mergers of firms that mainly operate in the same segment are likely to generate efficiency losses. Efficiency gains most likely result from reductions in material and labor costs, especially on a short- and mid-term perspective. The analysis of conditions that predict efficiency gains indicates that firm that announce the merger themselves are capable to generate efficiency gains in a short- and mid-term perspective. Furthermore, buyers that are mid-sized firms are more likely to generate efficiency gains than small or large buyers. Results also indicate that capital intense firms are likely to generate efficiency gains after a merger.
The present study is structured as follows.
Chapter 1 motivates the analysis of merger-specific efficiency gains. The definition of conditions that reasonably likely predict when and to which extent mergers will result in merger-specific efficiency gains, would improve the merger approval or denial process.
Chapter 2 gives a literature review of some relevant empirical studies that analyzed merger-specific efficiency gains. None of the empirical studies have analyzed horizontal mergers of European firms in the manufacturing sector in the years 2005 to 2014. Thus, the present study contributes to the existing literature by analyzing efficiency gains from those mergers.
Chapter 3 focuses on the identification of mergers. The merger term is defined according to the EC Merger Regulation and the Horizontal Merger Guidelines. The definition and the requirements of mergers according to legislation provides the framework of merger identification.
Chapter 4 concentrates on the efficiency measurement methodology. Most empirical studies apply a Total Factor Productivity (TFP) approach to estimate efficiency. The TFP approach uses linear regression in combination with a control function approach. The estimation of coefficients is done by a General Method of Moments approach.
The resulting efficiency estimates are used in the analysis of merger-specific efficiency gains in chapter 5. This analysis is done separately for buyers and targets by applying a Difference-In-Difference (DID) approach.
Chapter 6 concentrates on an alternative approach to estimate efficiency, that is a Stochastic Frontier Analysis (SFA) approach. Comparable to the TFP approach, the SFA approach is a stochastic efficiency estimation methodology. In contrast to TFP, SFA estimates the production function as a frontier function instead of an average function. The frontier function allows to estimate efficiency in percent.
Chapter 7 analyses the impact of different merger- and firm-specific characteristics on efficiency changes of buyers and targets. The analysis is based on a multiple regression, which is applied for short-, mid- and long-term efficiency changes of buyers and targets.
Chapter 8 concludes.
This dissertation deals with composite-based methods for structural equation models with latent variables and their enhancement. It comprises five chapters. Besides a brief introduction in the first chapter, the remaining chapters consisting of four essays cover the results of my PhD studies.Two of the essays have already been published in an international journal.
The first essay considers an alternative way of construct modeling in structural equation modeling.While in social and behavioral sciences theoretical constructs are typically modeled as common factors, in other sciences the common factor model is an inadequate way construct modeling due to its assumptions. This essay introduces the confirmatory composite analysis (CCA) analogous to confirmatory factor analysis (CFA). In contrast to CFA, CCA models theoretical constructs as composites instead of common factors. Besides the theoretical presentation of CCA and its assumptions, a Monte Carlo simulation is conducted which demonstrates that misspecifications of the composite model can be detected by the introduced test for overall model fit.
The second essay rises the question of how parameter differences can be assessed in the framework of partial least squares path modeling. Since the standard errors of the estimated parameters have no analytical closed-form, the t- and F-test known from regression analysis cannot be directly used to test for parameter differences. However, bootstrapping provides a solution to this problem. It can be employed to construct confidence intervals for the estimated parameter differences, which can be used for making inferences about the parameter difference in the population. To guide practitioners, guidelines were developed and demonstrated by means of empirical examples.
The third essay answers the question of how ordinal categorical indicators can be dealt with in partial least squares path modeling. A new consistent estimator is developed which combines the polychoric correlation and partial least squares path modeling to appropriately deal with the qualitative character of ordinal categorical indicators. The new estimator named ordinal consistent partial least squares combines consistent partial least squares with ordinal partial least squares. Besides its derivation, a Monte Carlo simulation is conducted which shows that the new estimator performs well in finite samples. Moreover, for illustration, an empirical example is estimated by ordinal consistent partial least squares.
The last essay introduces a new consistent estimator for polynomial factor models.
Similarly to consistent partial least squares, weights are determined to build stand-ins for the latent variables, however a non-iterative approach is used.
A Monte Carlo simulation shows that the new estimator behaves well in finite samples.
This dissertation consists of three contributions. Each addresses one specific aspect of intergenerational income mobility and is intended to be a stand-alone analysis. All chapters use comparable data for Germany and the United States to conduct country comparisons. As there are usually a large number of studies available for the United States, this approach is useful for comparing the empirical results to the existing literature.
The first part conducts a direct country comparison of the structure and extent of intergenerational income mobility in Germany and the United States. In line with existing results, the estimated intergenerational income mobility of 0.49 in the United States is significantly higher than that of 0.31 in Germany. While the results for the intergenerational rank mobility are relatively similar, the level of intergenerational income share mobility is higher in the United States than in Germany. There are no significant indications of a nonlinear run of intergenerational income elasticity. A final decomposition of intergenerational income inequality shows both greater income mobility and stronger progressive income growth for Germany compared to the United States. Overall, no clear ranking of the two countries can be identified. To conclude, several economic policy recommendations to increase intergenerational income mobility in Germany are discussed.
The second part examines the transmission channels of intergenerational income persistence in Germany and the United States. In principle, there are two ways in which well-off families may influence the adult incomes of their children: first through direct investments in their children's human capital (investment effect ), and second through the indirect transmission of human capital from parents to children (endowment effect ). In order to disentangle these two effects, a descriptive as well as a structural decomposition method are utilized. The results suggest that the investment effect and the endowment effect each account for approximately half of the estimated intergenerational income elasticity in Germany, while the investment effect is substantially more influential in the United States with a share of around 70 percent. With regard to economic policy, these results imply that equality of opportunity for children born to poor parents cannot be reached by the supply of financial means alone. Conversely, an efficient policy must additionally substitute for the missing direct transmission of human capital within socio-economically weak families.
The third part explicitly focuses on the intergenerational income mobility among daughters. The restriction to men is commonly made in the empirical literature due to women‘s lower labor market participation. While most men work full-time, the majority of (married) women still work only part-time or not at all. Especially with the occurrence of assortative mating, daughters from well-off families are likely to marry rich men and might decide to reduce their labor supply as a result. Thus, the individual labor income of a daughter might not be a good indicator for her actual economic status. The baseline regression analysis shows a higher intergenerational income elasticity in Germany and a lower intergenerational income elasticity in the United States for women as compared to men. However, a separation by marital status reveals that in both countries unmarried women exhibit a higher intergenerational income elasticity than unmarried men, while married women feature a lower intergenerational income elasticity than married men. The reason for the lower mobility of unmarried women turns out to be a stronger human capital transmission from fathers to daughters than to sons. The higher mobility of married women is driven by a weaker human capital transmission and a higher labor supply elasticity with respect to spousal income for women as compared to men. In order to further study the effects of assortative mating, the subsample of married children is analyzed by different types of income. It shows that the estimated intergenerational income elasticity of children's household incomes is even higher than that of their individual incomes. This can be seen as an indication for strong assortative mating. If household income is interpreted as a measure of children‘s actual economic welfare, there are barely any differences between sons and daughters. The intergenerational income elasticity of spousal income with respect to parental income is again relatively high, which in turn supports the hypothesis of strong assortative mating. The elasticity of the sons-in-law with respect to their fathers-in-law in Germany is even higher than that of the sons with respect to their own fathers.