Confidence in the Phillips Curve (PC) as predictor of inflation developments along the business cycle has been shaken by recent “inflation puzzles” in advanced countries, such as the “missing disinflation” in the aftermath of the Great Recession and the “missing inflation” in the years of recovery, to which the Euro-Zone “excess deflation” during the post-crisis depression may be added. This paper proposes a newly specified Phillips Curve model, in which expected inflation, instead of being treated as an exogenous explanatory variable of actual inflation, is endogenized. The idea is simply that if the PC is used to foresee inflation, then its expectational component should in some way be the result of agents using the PC itself. As a consequence, the truly independent explanatory variables of inflation turn out to be the output gaps and the related forecast errors by agents, with notable empirical consequences. The model is tested with the Euro-Zone data 1999–2019 showing that it may provide a consistent explanation of the “inflation puzzles” by disentangling the structural component from the expectational effects of the PC.

Young entrepreneurial firms are of critical importance for innovation. But to bring their new ideas to the market, these startups depend on investors who understand and are willing to accept the risk associated with a new firm. Perhaps the key reason as to why the US has succeeded in producing nearly all the most successful new firms of the 21st century is the economy’s ability to supply vast sums of capital to promising startups. The volume of venture capital (VC) invested in the US is more than 60 times that of Germany. In this policy note, we argue that differences in the regulatory and structural context of institutional investors, in particular life insurance companies, is a central driver of the relative lack of VC - and thereby successful startups - in Germany.

This paper documents behavioral differences in parental criminality between majority and minority ethnic groups after child birth. The particular effect we exploit is that of the gender of the first-born child on fathers’ convictions rates. Based on detailed judicial and demographic data from New Zealand, we first show that the previously documented inverse relationship between having a son and father’s criminal behaviour holds across the average of the population. However, when splitting the fathers’ sample by ethnicity, the effect appears to be entirely driven by the white part of the population and that there is no effect on the native Maori. The strong ethnic divide is observed along many dimensions and challenges the implicitly made assumption in the economics of crime literature that findings are universally applicable across cultures and race.

Modern market economies are characterized by the reallocation of resources from less productive, less valuable activities to more productive, more valuable ones. Businesses in the High Tech sector play a particularly important role in this reallocation by introducing new products and services that impact the entire economy. In this paper we describe an extension to the Census Bureau’s Business Dynamics Statistics that tracks job creation, job destruction, startups, and exits by firm and establishment characteristics, including sector, firm age, and firm size in the High Tech sector. We preview the resulting statistics, showing the structural shifts in the High Tech sector over the past 30 years, including the surge of entry and young firm activity in the 1990s that reversed abruptly in the early‐2000s.

Point estimates and error bands for SVARs that are set identified are only justified if the researcher is persuaded that some parameter values are a priori more plausible than others. When such prior information exists, traditional approaches can be generalized to allow for doubts about the identifying assumptions. We use information about both structural coefficients and impacts of shocks and propose a new asymmetric t-distribution for incorporating information about signs in a nondogmatic way. We apply these methods to a three-variable macroeconomic model and conclude that monetary policy shocks are not the major driver of output, inflation, or interest rates.

Even nearly 30 years after the fall of the Berlin Wall, the privatisation and transformation of East Germany's business landscape is controversially discussed in the media and politics. The privatisation process led to enormous structural changes, which were associated with massive job losses. In particular, the stagnating regional development of East Germany is often blamed on the “long shadow” of the privatisation activities of the Treuhandanstalt (THA). From a scientific perspective, however, there are hardly any contributions dealing with the effects of privatisation activities. The IWH-Treuhand Privatisation Micro Database introduced in this technical report is novel as such that it provides comprehensive information on employment and turnover figures for formerly state-owned enterprises for the early 1990s.

This paper is the first to study the effects of capital account liberalization on structural transformation and compare the contribution of within term and structural term to economic growth. We use a 10-sector-level productivity dataset to decomposes the effects of opening capital account on within-sector productivity growth and cross-sector structural transformation. We find that opening capital account is associated with labor productivity and employment share increment in sectors with higher human capital intensity and external financial dependence, as well as non-tradable sectors. But it results in a growth-reducing structural transformation by directing labor into sectors with lower productivity. Moreover, in the ten years after capital account liberalization, the contribution share of structural transformation decreases while that of within productivity growth increases. We conclude that the relationship between capital account liberalization and economic growth is within gain and structural pain.

In this paper we analyze the small sample properties of full information and limited information estimators in a potentially misspecified DSGE model. Therefore, we conduct a simulation study based on a standard New Keynesian model including price and wage rigidities. We then study the effects of omitted variable problems on the structural parameter estimates of the model. We find that FIML performs superior when the model is correctly specified. In cases where some of the model characteristics are omitted, the performance of FIML is highly unreliable, whereas GMM estimates remain approximately unbiased and significance tests are mostly reliable.

This paper investigates a perception in the political debates as to what extent poor countries are affected by price movements in the global commodity markets. To test this perception, we use the case of India to establish in a standard SVAR model that global food prices influence aggregate prices and food prices in India. To further analyze these empirical results, we specify a small open economy New-Keynesian model including oil and food prices and estimate it using observed data over the period from 1996Q2 to 2013Q2 by applying Bayesian estimation techniques. The results suggest that big part of the variation in inflation in India is due to cost-push shocks and, mainly during the years 2008 and 2010, also to global food price shocks, after having controlled for exogenous rainfall shocks. We conclude that the inflationary supply shocks (cost-push, oil price, domestic food price and global food price shocks) are important contributors to inflation in India. Since the monetary authority responds to these supply shocks with a higher interest rate which tends to slow growth, this raises concerns about how such output losses can be prevented by reducing exposure to commodity price shocks and thereby achieve higher growth.

We propose a unified identification scheme to identify monetary shocks and track their propagation through the economy. We combine three approaches dealing with the consequences of monetary shocks. First, we adjust a state space version of the P-star type model employing money overhang as the driving force of inflation. Second, we identify the contemporaneous impact of monetary policy shocks by applying a sign restriction identification scheme to the reduced form given by the state space signal equations. Third, to ensure that our results are not distorted by the measurement error exhibited by the official monetary data, we employ the Divisia M4 monetary aggregate provided by the Center for Financial Stability. Our approach overcomes one of the major difficulties of previous models by using a data-driven identification of equilibrium velocity. Thus, we are able to show that a P-star model can fit U.S. data and money did indeed matter in the United States.