Times of high unemployment always inspire debates on the role of labor market policy and most of the time lead to a variety of policy advice. The motivation of this work stems from the on-going controversy about optimal policy instruments for Germany that experienced a dramatic increase in unemployment during the years 2000 to 2005. While people agree that especially the rate of low-skilled unemployment is excessively high and current policy is suboptimal and leaves room for improvement, opinions on what should be done are mostly at odds with each other. Take as an example debate the Sinn et al. (2006) versus Brown et al. (2007). While the former prefer wage subsidies targeted at persons with low abilities, the latter favor hiring subsidies for long-term unemployed workers with low skills. Other empirical studies suggest that the effectiveness of both subsidies is limited. Bonin et al. (2002) find that wage subsidies for low-skilled workers in order to decrease disincentives do not appear to work very effectively and that such a policy is likely to be too costly. Boockmann et al. (2007) draw their conclusions from legal changes in the eligibility of German workers to EGZ which they use as natural experiments. They find that eligibility to this subsidy did not change the transition rates from unemployment to employment significantly. However, named empirical studies provide limited conclusion concerning the macroeconomic effects of hiring and wage subsidies as they cannot directly measure the effect of the subsidies in question, because they have never been implemented Germany-wide.
Cahuc and Le Barbanchon (2010), in their study on counseling, very well notice that micro evaluations neglecting crowding out, adverse spill over effects on non-targeted persons, and other equilibrium effects can lead to misguided policy advice. A similar point is made by Van der Linden (2005) who endogenizes job search effort and wages in his evaluation. In addition, the sort of studies mentioned above tends to lack a thorough evaluation of the cost side. Therefore, we base our analysis on a model of equilibrium unemployment and our conclusions rely on theoretical reasoning and numerical simulations.
Illegal immigration has become a topic of worldwide controversy in recent years. Whether it is concerned with the migration of Bangladeshis to India, Albanians to Greece, North Africans to Italy, or Mexicans to the United States, host country governments are rushing to define policies intended to curtail illegal immigration.
In the United States, a prolonged debate over the issue has led to two major immigration policy initiatives: the 1986 Immigration Reform and Control Act (IRCA), and the 1996 Illegal Immigration Reform and Immigrant Responsibility Act. Despite this legislation, the debate on the role of undocumented workers in the American labor market rages on.
Reliable leading indicators of the business cycle are of great importance for policy makers, firms, and investors. It is therefore not surprising that economists set out on an intensive quest for such leading indicators, ever since the initial attempts of Mitchell and Burns (1938) for the US economy. This research has provided much insight into the construction, use, and evaluation of leading indicators, see Marcellino (2006) for a recent survey.
Reliability of a leading indicator variable includes aspects such as consistency and timeliness. By consistency we refer to the property that a leading indicator should systematically give an accurate indication of the future course of the economy and should not produce false turning point signals too frequently, for example. Timeliness means that in order to be useful, a leading indicator variable should have a considerable lead time with respect to business cycle turning points. Most of the currently popular leading indicator variables are believed to have a lead time between six and eighteen months. At the same time, it appears to be the case that many of these variables have a considerably longer lead time at business cycle peaks than at troughs. For example, the Composite Index of Leading Indicators (CLI) currently published by The Conference Board has led cyclical downturns in the economy by eight to twenty months, and upturns by one to ten months during the post-World War II period (The Conference Board, 2001).
