We propose a resolution of the missing deflation puzzle. Our resolution stresses the importance of nonlinearities in price- and wage-setting when the economy is exposed to large shocks. We show that a nonlinear macroeconomic model with real rigidities resolves the missing deflation puzzle, while a linearized version of the same underlying nonlinear model fails to do so. In addition, our nonlinear model reproduces the skewness of inflation and other macroeconomic variables observed in post-war U.S. data. All told, our results caution against the common practice of using linearized models to study inflation and output dynamics.

We calculate the magnitude of the government consumption multiplier in linearized and nonlinear solutions of a New Keynesian model at the zero lower bound. Importantly, the model is amended with real rigidities to simultaneously account for the macroeconomic evidence of a low Phillips curve slope and the microeconomic evidence of frequent price changes. We show that the nonlinear solution is associated with a much smaller multiplier than the linearized solution in long‐lived liquidity traps, and pin down the key features in the model which account for the difference. Our results caution against the common practice of using linearized models to calculate fiscal multipliers in long‐lived liquidity traps.

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.

Noncompete agreements (also known as covenants not to compete [CNCs]) are frequently used by many businesses in an attempt to maintain their competitive advantage by safeguarding their human capital and the associated business secrets. Although the choice of whether to include CNCs in employment contracts is made by firms, the real extent of their restrictiveness is determined by the state laws. In this article, we explore the effect of state‐level CNC enforceability on firm productivity. We assert that an increase in state level CNC enforceability is detrimental to firm productivity, and this relationship becomes stronger as comparable job opportunities become more concentrated in a firm's home state. On the other hand, this negative relationship is weakened as employee compensation tends to become more long‐term oriented. Results based on hierarchical linear modeling analysis of 21,134 firm‐year observations for 3,027 unique firms supported all three hypotheses.

Early-warning models most commonly optimize signaling thresholds on crisis probabilities. The expost threshold optimization is based upon a loss function accounting for preferences between forecast errors, but comes with two crucial drawbacks: unstable thresholds in recursive estimations and an in-sample overfit at the expense of out-of-sample performance. We propose two alternatives for threshold setting: (i) including preferences in the estimation itself and (ii) setting thresholds ex-ante according to preferences only. Given probabilistic model output, it is intuitive that a decision rule is independent of the data or model specification, as thresholds on probabilities represent a willingness to issue a false alarm vis-à-vis missing a crisis. We provide simulated and real-world evidence that this simplification results in stable thresholds and improves out-of-sample performance. Our solution is not restricted to binary-choice models, but directly transferable to the signaling approach and all probabilistic early-warning models.

We document that expansionary monetary policy shocks are less effective at stimulating output and investment in periods of high volatility compared to periods of low volatility, using a regime-switching vector autoregression. Exogenous policy changes are identified by adapting an external instruments approach to the non-linear model. The lower effectiveness of monetary policy can be linked to weaker responses of credit costs, suggesting a financial accelerator mechanism that is weaker in high volatility periods. To rationalize our robust empirical results, we use a macroeconomic model in which financial intermediaries endogenously choose their capital structure. In the model, the leverage choice of banks depends on the volatility of aggregate shocks. In low volatility periods, financial intermediaries lever up, which makes their balance sheets more sensitive to aggregate shocks and the financial accelerator more effective. On the contrary, in high volatility periods, banks decrease leverage, which renders the financial accelerator less effective; this in turn decreases the ability of monetary policy to improve funding conditions and credit supply, and thereby to stimulate the economy. Hence, we provide a novel explanation for the non-linear effects of monetary stimuli observed in the data, linking the effectiveness of monetary policy to the procyclicality of leverage.

In the wake of the recent financial crisis, significant regulatory actions have been taken aimed at limiting risks emanating from trading in bank business models. Prominent reform proposals are the Volcker Rule in the U.S., the Vickers Report in the UK, and, based on the Liikanen proposal, the Barnier proposal in the EU. A major element of these reforms is to separate “classical” commercial banking activities from securities trading activities, notably from proprietary trading. While the reforms are at different stages of implementation, there is a strong ongoing discussion on what possible economic consequences are to be expected. The goal of this paper is to look at the alternative approaches of these reform proposals and to assess their likely consequences for bank business models, risk-taking and financial stability. Our conclusions can be summarized as follows: First, the focus on a prohibition of only proprietary trading, as envisaged in the current EU proposal, is inadequate. It does not necessarily reduce risk-taking and it likely crowds out desired trading activities, thereby negatively affecting financial stability. Second, there is potentially a better solution to limit excessive trading risk at banks in terms of potential welfare consequences: Trading separation into legally distinct or ring-fenced entities within the existing banking organizations. This kind of separation limits cross-subsidies between banking and proprietary trading and diminishes contagion risk, while still allowing for synergies across banking, non-proprietary trading and proprietary trading.

The focus of this paper is on the steady state of a two-sector economy with undirected search where employed and unemployed workers can search for jobs, both within a sector and between the sectors. As in the one-sector model, on-the-job search generates wage dispersion among homogeneous workers. The analysis of the two-sector model uncovers a property called constant tension that is responsible for analytical tractability. We characterize the steady state in all cases with constant tension. When time discounting vanishes, constant tension yields the endogenous separation rate in each sector as a linear function of the present value for a worker. The one-sector economy automatically satisfies constant tension, in which case the linear separation rate implies that equilibrium offers of the worker value are uniformly distributed. Constant tension also has strong predictions for worker transitions and value/wage dispersion, both within a sector and between the two sectors. When constant tension does not hold, we compute the steady state numerically and illustrate its properties.

Early-warning models most commonly optimize signaling thresholds on crisis probabilities. The ex-post threshold optimization is based upon a loss function accounting for preferences between forecast errors, but comes with two crucial drawbacks: unstable thresholds in recursive estimations and an in-sample overfit at the expense of out-of-sample performance. We propose two alternatives for threshold setting: (i) including preferences in the estimation itself and (ii) setting thresholds ex-ante according to preferences only. We provide simulated and real-world evidence that this simplification results in stable thresholds and improves out-of-sample performance. Our solution is not restricted to binary-choice models, but directly transferable to the signaling approach and all probabilistic early-warning models.

This paper analyses the determinants of spatial distribution of foreign technological activity across 96 German regions (1996-2009). We identify foreign inventive activity by applying the ‘cross-border-ownership concept’ to transnational patent applications. The descriptive analysis shows that foreign technological activity more than doubled during the observation period with persistent spatial heterogeneity in Germany. Using a pooled count data model, we estimate the effect of various sources for externalities on the extent of foreign technological activity across regions. Our results show that foreign technological activity is attracted by technologically specialised sectors of regions. In contrast to existing findings this effect applies both to foreign as well as domestic sources of specialisation. We show that the relation between specialisation and foreign technological activity is non-linear and that it is influenced by sectoral heterogeneity. Externalities related to technological diversification attract foreign R&D only into ‘higher order’ regions.