This paper investigates the relationship between product market competition and innovation. We find strong evidence of an inverted-U relationship using panel data. We develop a model where competition discourages laggard firms from innovating but encourages neck-and-neck firms to innovate. Together with the effect of competition on the equilibrium industry structure, these generate an inverted-U. Two additional predictions of the model-that the average technological distance between leaders and followers increases with competition, and that the inverted-U is steeper when industries are more neck-and-neck-are both supported by the data

This paper investigates the relationship between product market competition and innovation. We find strong evidence of an inverted-U relationship using panel data. We develop a model where competition discourages laggard firms from innovating but encourages neck-and-neck firms to innovate. Together with the effect of competition on the equilibrium industry structure, these generate an inverted-U. Two additional predictions of the model—that the average technological distance between leaders and followers increases with competition, and that the inverted-U is steeper when industries are more neck-and-neck—are both supported by the data

We model an OLG economy where productivity growth comes from two alternative sources: process innovation and learning-by-doing. There is a trade-off between the two in so far as frequent technological updates reduce the scope for learning on existing technologies. A conflict is shown to arise between the young and the old, because the former favor innovation while the latter prefer learning. We model the interaction between different generations and short-lived policy makers as a dynamic common agency problem, where competing generations invest a certain amount of resources to lobby either for the maintainance of the current technology or the adoption of a new one. By focusing on truthful Markov perfect equilibria, we characterize the political equilibrium and show its dependence on the underlying technological parameters

The objective of this paper is to investigate whether financial innovation of credit derivatives makes banks more exposed to credit risk. Although credit derivatives are important for hedging and securitizing credit risk – and thereby likely to enhance the sharing of such risk – some commentators have raised concerns that they may destabilize the banking sector. This paper investigates this issue in a simple model driven by costs of financial distress. The analysis identifies two effects of credit derivatives innovation – they enhance risk sharing as suggested by the hedging argument – but they also make further acquisition of risk more attractive. The latter effect, if dominant, can therefore destabilize the banking sector. The critical factor is, perhaps surprisingly, the competitive nature of the existing underlying credit markets. As these markets become more elastic the threat of destabilization increases. The paper discusses issues related to bank regulation within the context of the model

Structural vector autoregressions (VARs) are widely used to trace out the effect of monetary policy innovations on the economy.However, the sparse information sets typically used in these empirical models lead to at least two potential problems with the results.First, to the extent that central banks and the private sector have information not reflected in the VAR, the measurement of policy innovations is likely to be contaminated.A second problem is that impulse responses can be observed only for the included variables, which generally constitute only a small subset of the variables that the researcher and policymaker care about.In this paper we investigate one potential solution to this limited information problem, which combines the standard structural VAR analysis with recent developments in factor analysis for large data sets.We find that the information that our factor-augmented VAR (FAVAR) methodology exploits is indeed important to properly identify the monetary transmission mechanism.Overall, our results provide a comprehensive and coherent picture of the effect of monetary policy on the economy

Structural vector autoregressions (VARs) are widely used to trace out the effect of monetary policy innovations on the economy. However, the sparse information sets typically used in these empirical models lead to at least three potential problems with the results. First, to the extent that central banks and the private sector have information not reflected in the VAR, the measurement of policy innovations is likely to be contaminated. Second, the choice of a specific data series to represent a general economic concept such as “real activity” is often arbitrary to some degree. Third, impulse responses can be observed only for the included variables, which generally constitute only a small subset of the variables that the researcher and policy-maker care about. In this paper we investigate one potential solution to this limited information problem, which combines the standard structural VAR analysis with recent developments in factor analysis for large data sets. We find that the information that our factor-augmented VAR (FAVAR) methodology exploits is indeed important to properly identify the monetary transmission mechanism. Overall, our results provide a comprehensive and coherent picture of the effect of monetary policy on the economy

This article explores cross-market liquidity dynamics by estimating a vector autoregressive model for liquidity (bid-ask spread and depth, returns, volatility, and order flow in the stock and Treasury bond markets). Innovations to stock and bond market liquidity and volatility are significantly correlated, implying that common factors drive liquidity and volatility in these markets. Volatility shocks are informative in predicting shifts in liquidity. During crisis periods, monetary expansions are associated with increased liquidity. Moreover, money flows to government bond funds forecast bond market liquidity. The results establish a link between "macro" liquidity, or money flows, and "micro" or transactions liquidity

This paper studies the mutual fund industry in 56 countries and examines where this financial innovation has flourished. The fund industry is larger in countries with stronger rules, laws, and regulations, and specifically where mutual fund investors’ rights are better protected. The industry is also larger in countries with wealthier and more educated populations, where the industry is older, trading costs are lower and in which defined contribution pension plans are more prevalent. The industry is smaller in countries where barriers to entry are higher. These results indicate that laws and regulations, supply-side and demand-side factors simultaneously affect the size of the fund industry