In this paper, we analyse the effects of the stimulus packages adopted by the German government during the Great Recession. We employ a standard medium-scale dynamic stochastic general equilibrium (DSGE) model extended by non-optimising households and a detailed fiscal sector. In particular, the dynamics of spending and revenue variables are modeled as feedback rules with respect to the cyclical component of output. Based on the estimated rules, fiscal shocks are identified. According to the results, fiscal policy, in particular public consumption, investment, transfers and changes in labour tax rates including social security contributions prevented a sharper and prolonged decline of German output at the beginning of the Great Recession, suggesting a timely response of fiscal policy. The overall effects, however, are small when compared to other domestic and international shocks that contributed to the economic downturn. Our overall findings are not sensitive to the allowance of fiscal foresight.

Why does job displacement, e.g., following import competition, technological change, or economic downturns, result in permanent wage losses? The job displacement literature is silent on whether wage losses after job displacement are driven by lost firm wage premiums or worker productivity depreciations. We therefore estimate losses in wages and firm wage premiums. Premiums are measured as firm effects from a two-way fixed-effects approach, as described in Abowd, Kramarz, and Margolis (1999). Using German administrative data, we find that wage losses are, on average, fully explained by losses in firm wage premiums and that premium losses are largely permanent. We show that losses in wages and premiums are minor for workers displaced from small plants and strongly increase with pre-displacement firm size, which provides an explanation for the large and persistent wage losses that have been found in previous studies mostly focusing on displacement from large employers.

We present a field experiment in which we set up a call-center to study how the productivity of workers is affected if managers treat their co-workers in an unfair way. This question cannot be studied in long-lived organizations since workers may change their career expectations (and hence effort) when managers behave unfairly towards co-workers. In order to rule out such confounds and to measure productivity changes of unaffected workers in a clean way, we create an environment where employees work for two shifts. In one treatment, we lay off parts of the workforce before the second shift. Compared to two different control treatments, we find that, in the layoff treatment, the productivity of the remaining, unaffected workers drops by 12 percent. We show that this result is not driven by peer effects or altered beliefs about the job or the managers’ competence, but rather related to the workers’ perception of unfair behavior of employers towards co-workers. The latter interpretation is confirmed in a survey among professional HR managers. We also show that the effect of unfair behavior on the productivity of unaffected workers is close to the upper bound of the direct effects of wage cuts on the productivity of affected workers. This suggests that the price of an employer’s unfair behavior goes well beyond the potential tit-for-tat of directly affected workers.

With advanced economies likely to face over-utilization of economic capacities in 2018 for the first time since the Great Recession, companies will further expand their investment activities. Price and wage dynamics will pick up globally, triggered by the recent increase in energy prices. A major risk for the world economy pertains to financial markets: measures for risk tolareance and valuations for many types of assets have approached levels last reached ten years ago, on the eve of the financial crisis. A sudden readjustment of asset prices and risk premia could worsen financial conditions globally and seriously affect the global economy. The cyclical upswing of the euro area economy continues. The recovery, under way since summer 2013, transformed into an upswing in autumn 2016 when demand from outside the euro area increased quite abruptly; higher exports and improved expectations have contrinuted to induce firms to invest more into equipment. Wage dynamics in the euro area appear to increase, but only slowly. An annual growth rate for hourly wage costs of about 2% is still not enough to put upward pressure on prices, but this will change eventually as the cyclical upswing is likely to continue. Inflation will, according to our forecast, reach the ECB’s target of below but close to 2% in the second half of 2019. Conditions for further healthy growth in the euro area are in place, but employment dynamics might markedly lose momentum in some member countries in the second half of 2018, as the potential labour force is becoming more and more exhausted. Overall, we forecast euro area GDP to grow by 2.2% in 2018 and by 1.5% in 2019.

Ample evidence indicates that a person’s human capital is important for success on the labor market in terms of both wages and employment prospects. However, unlike the efforts to identify the impact of school attainment on labor-market outcomes, the literature on returns to cognitive skills has not yet provided convincing evidence that the estimated returns can be causally interpreted. Using the PIAAC Survey of Adult Skills, this paper explores several approaches that aim to address potential threats to causal identification of returns to skills, in terms of both higher wages and better employment chances. We address measurement error by exploiting the fact that PIAAC measures skills in several domains. Furthermore, we estimate instrumental-variable models that use skill variation stemming from school attainment and parental education to circumvent reverse causation. Results show a strikingly similar pattern across the diverse set of countries in our sample. In fact, the instrumental-variable estimates are consistently larger than those found in standard least-squares estimations. The same is true in two “natural experiments,” one of which exploits variation in skills from changes in compulsory-schooling laws across U.S. states. The other one identifies technologically induced variation in broadband Internet availability that gives rise to variation in ICT skills across German municipalities. Together, the results suggest that least-squares estimates may provide a lower bound of the true returns to skills in the labor market.

In this paper we study the relationship between task complexity and the occupational wage- and employment structure. Complex tasks are defined as those requiring higher-order skills, such as the ability to abstract, solve problems, make decisions, or communicate effectively. We measure the task complexity of an occupation by performing Principal Component Analysis on a broad set of occupational descriptors in the Occupational Information Network (O*NET) data. We establish four main empirical facts for the U.S. over the 1980–2005 time period that are robust to the inclusion of a detailed set of controls, subsamples, and levels of aggregation: (1) There is a positive relationship across occupations between task complexity and wages and wage growth; (2) Conditional on task complexity, routine-intensity of an occupation is not a significant predictor of wage growth and wage levels; (3) Labor has reallocated from less complex to more complex occupations over time; (4) Within groups of occupations with similar task complexity labor has reallocated to non-routine occupations over time. We then formulate a model of Complex-Task Biased Technological Change with heterogeneous skills and show analytically that it can rationalize these facts. We conclude that workers in non-routine occupations with low ability of solving complex tasks are not shielded from the labor market effects of automatization.