Disparate Wages in a Globalized World

This study uses wage data from the UBS Prices and Earnings survey to highlight Disparate Wages in a Globalized World from di↵erent perspectives. This wage data is characterised by remarkable consistency over the last 40 years, as well as unusual global comparability. In the first chapter we analyse the convergence hypothesis for purchasing power adjusted wages across the world for 1970 to 2009. The results provide solid evidence for the hypotheses of absolute and conditional convergence in real wages, with the key driver being faster overall growing wage levels in lower wage countries compared to higher wage countries. At the same time, the highest skilled professions have experienced the highest wage growth, while low skilled workers’ wages have lagged, thus no convergence in this sense is found between skill groups. In the second chapter we examine deviations in international wages from Factor Price Equalisation theory (FPE). Following an approach analogous to Engel (1993) we find that deviations from FPE are more likely driven by the higher variability of wages between countries than by the variability of di↵erent wages within countries. With regard to the traditional analysis of the real exchange rate and the Balassa-Samuelson assumptions our analysis points to a larger impact on the real exchange rate likely stemming from the movements in the real exchange rate of tradables, and only to a lesser extent from the lack of equalisation of wages within countries. In the third chapter our results show that India’s economic and trade liberalisation, starting in the early 1990s, had very di↵erential impacts on skill premia, both over time and over skill levels. The most striking result is the large increase in wage inequality of high-skilled versus low-skilled professions. Both the synthetic control group method and the di↵erence-in-di↵erences (DID) approach suggest that a significant part of this increase in wage inequality can be attributed to India’s liberalisation.

Is choking under pressure a consequence of skill-focus or increased distractibility? Results from a tennis serve task

It has been repeatedly demonstrated that athletes often choke in high pressure situations because anxiety can affect attention regulation and in turn performance. There are two competing theoretical approaches to explain the negative anxiety-performance relationship. According to skillfocus theories, anxious athletes’ attention is directed at how to execute the sport-specific movements which interrupts execution of already automatized movements in expert performers. According to distraction theories, anxious athletes are distractible and focus less on the relevant stimuli. We tested these competing assumptions in a between-subject design, as semi-professional tennis players were either assigned to an anxiety group (n = 25) or a neutral group (n = 28), and performed a series of second tennis serves into predefined target areas. As expected, anxiety was negatively related to serve accuracy. However, mediation analyses with the bootstrapping method revealed that this relationship was fully mediated by self-reported distraction and not by skill-focus.

Establishing the skill of climate field reconstruction techniques for precipitation with pseudoproxy experiments

This study aims at assessing the skill of several climate field reconstruction techniques (CFR) to reconstruct past precipitation over continental Europe and the Mediterranean at seasonal time scales over the last two millennia from proxy records. A number of pseudoproxy experiments are performed within the virtual reality ofa regional paleoclimate simulation at 45 km resolution to analyse different aspects of reconstruction skill. Canonical Correlation Analysis (CCA), two versions of an Analog Method (AM) and Bayesian hierarchical modeling (BHM) are applied to reconstruct precipitation from a synthetic network of pseudoproxies that are contaminated with various types of noise. The skill of the derived reconstructions is assessed through comparison with precipitation simulated by the regional climate model. Unlike BHM, CCA systematically underestimates the variance. The AM can be adjusted to overcome this shortcoming, presenting an intermediate behaviour between the two aforementioned techniques. However, a trade-off between reconstruction-target correlations and reconstructed variance is the drawback of all CFR techniques. CCA (BHM) presents the largest (lowest) skill in preserving the temporal evolution, whereas the AM can be tuned to reproduce better correlation at the expense of losing variance. While BHM has been shown to perform well for temperatures, it relies heavily on prescribed spatial correlation lengths. While this assumption is valid for temperature, it is hardly warranted for precipitation. In general, none of the methods outperforms the other. All experiments agree that a dense and regularly distributed proxy network is required to reconstruct precipitation accurately, reflecting its high spatial and temporal variability. This is especially true in summer, when a specifically short de-correlation distance from the proxy location is caused by localised summertime convective precipitation events.

DECOMPOSE: Stata module to compute decompositions of wage differentials

Given the results from two regressions (one for each of two groups), decompose computes several decompositions of the outcome variable differential. The decompositions shows how much of the gap is due to differing endowments between the two groups, and how much is due to discrimination. Usually this is applied to wage differentials using Mincer type earnings equations.