>>A completely revised version of this paper has been published as: Dettmann, Eva; Giebler, Alexander; Weyh, Antje: flexpaneldid. A Stata Toolbox for Causal Analysis with Varying Treatment Time and Duration. IWH Discussion Paper 3/2020. Halle (Saale) 2020.<<

The paper presents a modification of the matching and difference-in-differences approach of Heckman et al. (1998) and its Stata implementation, the command flexpaneldid. The approach is particularly useful for causal analysis of treatments with varying start dates and varying treatment durations (like investment grants or other subsidy schemes). Introducing more flexibility enables the user to consider individual treatment and outcome periods for the treated observations. The flexpaneldid command for panel data implements the developed flexible difference-in-differences approach and commonly used alternatives like CEM Matching and difference-in-differences models. The novelty of this tool is an extensive data preprocessing to include time information into the matching approach and the treatment effect estimation. The core of the paper gives two comprehensive examples to explain the use of flexpaneldid and its options on the basis of a publicly accessible data set.

This article examines how trade shocks shape labour market imperfections that create market power in labour markets and prevent an efficient allocation of labour. I develop a framework for measuring such labor market distortions in monetary terms and document large degrees of those distortions in Germany’s manufacturing sector. Import competition can only exert labor market disciplining effects when firms rather than workers have labour market power. Otherwise, export demand and import competition shocks tend to fortify existing distortions by amplifying labour market power structures. This diminishes the gains from trade compared to a model with perfectly competitive labour markets.

Interactive regional learning involving various actors is considered a precondition for successful innovations and, hence, for regional development. Diasporas as non-native ethnic groups are regarded as beneficial since they enrich the creative class by broadening the cultural base and introducing new routines. Using data on research and development (R&D) collaboration projects, the analysis provides tentative evidence that the size of diasporas positively affects the region’s share of outward R&D linkages enabling the exchange of knowledge. The empirical analysis further confirms that these interactions mainly occur between regions hosting the same diasporas, pointing to a positive effect of ethnic proximity rather than ethnic diversity.

Can a negative shock to sovereign ratings invoke a vicious cycle of increasing government bond yields and further downgrades, ultimately pushing a country toward default? The narratives of public and political discussions, as well as of some widely cited papers, suggest this possibility. In this paper, we will investigate the possible existence of such a vicious cycle. We find no evidence of a bad long-run equilibrium and cannot confirm a feedback loop leading into default as a transitory state for all but the very worst ratings. We use a bivariate semiparametric dynamic panel model to reproduce the joint dynamics of sovereign ratings and government bond yields. The individual equations resemble Pesaran-type cointegration models, which allow for valid interference regardless of whether the employed variables display unit-root behavior. To incorporate most of the empirical features previously documented (separately) in the literature, we allow for different long-run relationships in both equations, nonlinearities in the level effects of ratings, and asymmetric effects in changes of ratings and yields. Our finding of a single good equilibrium implies the slow convergence of ratings and yields toward this equilibrium. However, the persistence of ratings is sufficiently high that a rating shock can have substantial costs if it occurs at a highly speculative rating or lower. Rating shocks that drive the rating below this threshold can increase the interest rate sharply, and for a long time. Yet, simulation studies based on our estimations show that it is highly improbable that rating agencies can be made responsible for the most dramatic spikes in interest rates.

We analyze the effect of monetary policy transparency on bilateral exchange rate volatility. We test the theoretical predictions of a stylized model using panel data for 62 currencies from 1998 to 2010. We find strong evidence that an increase in the availability of information about monetary policy objectives decreases exchange rate volatility. Using interaction models, we find that this effect is more pronounced for countries with a lower flexibility of goods prices, a lower level of central bank conservatism, and a higher interest rate sensitivity of money demand.

This article examines how trade shocks shape labour market imperfections that create market power in labour markets and prevent an efficient allocation of labour. I develop a framework for measuring such labour market distortions in monetary terms and document large degrees of those distortions in Germany’s manufacturing sector. Import competition can only exert labour market disciplining effects when firms rather than workers have labour market power. Otherwise, export demand and import competition shocks tend to fortify existing distortions by amplifying labour market power structures. This diminishes the gains from trade compared to a model with perfectly competitive labour markets.

In this paper, we use the panel of the first two waves of the Household Finance and Consumption Survey by the European Central Bank to study housing demand of European households and evaluate potential housing market regulations in the post-crisis era. We provide a comprehensive account of the housing decisions of European households between 2010 and 2014, and structurally estimate the housing preference of a simple life-cycle housing choice model. We then evaluate the effect of a tighter LTV/LTI regulation via counter-factual simulations. We find that those regulations limit homeownership and wealth accumulation, reduces housing consumption but may be welfare improving for the young households.

Since the global financial crisis, monetary economics new questions include the explanation and response to unusual consumer price developments but also the interdependencies between financial markets and real economic activity and its implication for the monetary policy transmission mechanism. This dissertation investigates these questions by presenting empirical evidence that accounts for non-linearities of the relevant economic relations. The first and second chapters examine inflation dynamics of the Euro area and ASEAN-5 economies using non-linear Phillips curve models. The results suggest that changes in inflation processes are mainly driven by the development of long-term inflation expectations. The third chapter investigates the evolution of the financial accelerator (FA) taking into account the developments of the financial sector. The results of a time-varying structural vector autoregressive model indicate that the FA effect for the USA has increased from the early 1990s.

I develop a theoretical model to investigate the effect of simultaneous regulation with a leverage ratio and a risk-weighted ratio on banks‘ risk taking and banking market structure. I extend a portfolio choice model by adding heterogeneity in productivity among banks. Regulators face a trade-off between the efficient allocation of resources and financial stability. In an oligopolistic market, risk-weighted requirements incentivise banks with high productivity to lend to low-risk firms. When a leverage ratio is introduced, these banks lose market shares to less productive competitors and react with risk-shifting into high-risk loans. While average productivity in the low-risk market falls, market shares in the high-risk market are dispersed across new entrants with high as well as low productivity.

The outcome of any important macroeconomic policy change is the net effect of forces operating on different parts of the economy. A central challenge facing policymakers is how to assess the relative strength of those forces. Economists have a range of tools that can be used to make such assessments. Dynamic stochastic general equilibrium (DSGE) models are the leading tool for making such assessments in an open and transparent manner. We review the state of mainstream DSGE models before the financial crisis and the Great Recession. We then describe how DSGE models are estimated and evaluated. We address the question of why DSGE modelers—like most other economists and policymakers—failed to predict the financial crisis and the Great Recession, and how DSGE modelers responded to the financial crisis and its aftermath. We discuss how current DSGE models are actually used by policymakers. We then provide a brief response to some criticisms of DSGE models, with special emphasis on criticism by Joseph Stiglitz, and offer some concluding remarks.