Unemployment and house price crises: Lessons for Fiscal Policy from the Dutch Recession

Since the beginning of the financial crisis in 2008, the Dutch economy lost 6% of gdp relative to Germany, even though the Netherlands (unlike the GIPSI countries) did not face serious problems to finance its sovereign debt. This bad performance is explained by the interaction of fiscal policy and the housing market. This makes the Netherlands an interesting case because these effects can be analyzed in isolation of stress on financial markets. We sketch a simple overlapping generation framework. House price declines lead to a temporary drop in consumption, forcing a reallocation of labour from domestic to tradable industries. This leads to a loss in industry specific human capital, causing a jump in unemployment. The analysis yields a number of lessons for fiscal policy in the aftermath of a financial crisis and for the current EU framework for the evaluation of member states’ fiscal policy. Fiscal policy provided too little intergenerational insurance and the EU framework is an obstacle to do that.This is the final version of the article. It first appeared from Springer via http://dx.doi.org/10.1186/2193-9012-3-2

Monopolistic price-setting behavior of information technology firms

Markups, which are when prices are greater than the marginal cost of production, have increased in the USA over the last decades. Our paper explores the differences in markups between Information Technology (IT) and non-IT firms. By doing so, we contribute to the understanding of the role of the IT industry in the increase in markups. We extend to De Loecker, Eeckhout, and Unger (2020), who find that markups of publicly traded firms have risen since 1980. They argue that no industry has systematically higher markups. We develop a novel firm-level classification method using natural language processing (NLP) to distinguish IT from non-IT firms. Our approach differs from the commonly used North American Industry Classification System (NAICS). Using our classification, we find that the increase in markup in the period since 1980 occurred in two separate episodes. In the first, from 1980 until 1996, firms recovered from the fall of markups in the 1970s. In the second episode, since 1996, markups of IT firms diverge enormously. Markups of IT firms surge from 47% in 1996 to 80% in 2018, while the markup of non-IT firms remains largely unchanged