Local and global indeterminacy in two-sector models of endogenous growth

We consider a two-sector endogenous growth model where the productions of the final good and human capital require economy-wide external effects. Assuming constant returns to scale at the private and social levels, we show that local and global indeterminacy of equilibrium paths are compatible with any values for the elasticity of intertemporal substitution in consumption and any sign for the capital intensity difference across the two sectors. We also show that for any value of the elasticity of intertemporal substitution in consumption, poverty traps may occur when the final good sector is capital intensive in human capital.     

Knowledge spillovers in US patents: A dynamic patent intensity model with secret common innovation factors

During the past two decades, innovations protected by patents have played a key role in business strategies. This fact enhanced studies of the determinants of patents and the impact of patents on innovation and competitive advantage. Sustaining competitive advantages is as important as creating them. Patents help sustaining competitive advantages by increasing the production cost of competitors, by signaling a better quality of products and by serving as barriers to entry. If patents are rewards for innovation, more R&D should be reflected in more patent applications but this is not the end of the story. There is empirical evidence showing that patents through time are becoming easier to get and more valuable to the firm due to increasing damage awards from infringers. These facts question the constant and static nature of the relationship between R&D and patents. Furthermore, innovation creates important knowledge spillovers due to its imperfect appropriability. Our paper investigates these dynamic effects using US patent data from 1979 to 2000 with alternative model specifications for patent counts. We introduce a general dynamic count panel data model with dynamic observable and unobservable spillovers, which encompasses previous models, is able to control for the endogeneity of R&D and therefore can be consistently estimated by maximum likelihood. Apart from allowing for firm specific fixed and random effects, we introduce a common unobserved component, or secret stock of knowledge, that affects differently the propensity to patent of each firm across sectors due to their different absorptive capacity.     

The Barnett critique after three decades: A New Keynesian analysis

This paper extends a New Keynesian model to include roles for currency and deposits as competing sources of liquidity services demanded by households. It shows that, both qualitatively and quantitatively, the Barnett critique applies: while a Divisia aggregate of monetary services tracks the true monetary aggregate almost perfectly, a simple-sum measure often behaves quite differently. The model also shows that movements in both quantity and price indexes for monetary services correlate strongly with movements in output following a variety of shocks. Finally, the analysis characterizes the optimal monetary policy response to disturbances that originate in the financial sector.     

How does Monetary Policy Respond to Exchange Rate Movements? New International Evidence*

This article analyzes how monetary policy has responded to exchange rate movements in six open economies, paying particular attention to the two‐way interaction between monetary policy and the exchange rate. We address this issue using a structural VAR model that is identified using a combination of sign and short‐term (zero) restrictions. Doing so we find that, while there is a instantaneous reaction in the exchange rate following a monetary policy shock in all countries, monetary policy responds significantly on impact to an exchange rate shock in only four of the six countries.     

Regulatory risk, market uncertainties, and firm financing choices: Evidence from U.S. Electricity Market Restructuring

Based on the universe of rate-regulated electric utilities in the U.S., we examine why firms alter their financing decisions when transitioning from a regulated to a competitive market regime. We find that the significant increase in regulatory risk after the passage of the Energy Policy Act, state-level restructuring legislations, and divestiture policies have reduced leverage by 15 percent. Policies that encouraged competition, and hence increased market uncertainty, lowered leverage by another 13 percent on average. The ability to exercise market power allowed some firms to counter this competitive threat. In aggregate, regulatory risk and market uncertainty variables reduce leverage between 24.6 and 26.7 percent. We also confirm findings in the literature that firms with higher profitability and higher asset growth have lower leverage, and those with more tangible assets are more levered. Firms with greater access to internal capital markets and those with a footloose customer segment use less debt, while those actively involved in trading power in the wholesale market use more debt.     

How long do housing cycles last? A duration analysis for 19 OECD countries

This paper analyzes the duration of house price upturns and downturns in the last 40 years for 19 OECD countries. Both upturns and downturns display duration dependence: they are more likely to end as their duration increases. Downturns display also lagged duration dependence: they are less likely to end if the previous upturn was particularly long. These patterns are consistent with a boom-bust view of housing price dynamics, where booms represent departures from fundamentals that are increasingly difficult to sustain and busts serve as readjustment periods. Findings are robust to the inclusion of macroeconomic variables, which allow for the estimation of additional determinants of house price expansions and contractions.     

Trend/cycle decomposition of regime-switching processes

We present a new approach to trend/cycle decomposition of time series that follow regime-switching processes. The proposed approach, which we label the “regime-dependent steady-state” (RDSS) decomposition, is motivated as the appropriate generalization of the Beveridge and Nelson decomposition [Beveridge, S., Nelson, C.R., 1981. A new approach to decomposition of economic time series into permanent and transitory components with particular attention to measurement of the business cycle. Journal of Monetary Economics 7, 151–174] to the setting where the reduced-form dynamics of a given series can be captured by a regime-switching forecasting model. For processes in which the underlying trend component follows a random walk with possibly regime-switching drift, the RDSS decomposition is optimal in a minimum mean-squared-error sense and is more broadly applicable than directly employing an Unobserved Components model.     

Minimum Distance Estimation and Testing of DSGE Models from Structural VARs*

The aim of this paper is to complement the minimum distance estimation–structural vector autoregression approach when the weighting matrix is not optimal. In empirical studies, this choice is motivated by stochastic singularity or collinearity problems associated with the covariance matrix of impulse response functions. Consequently, the asymptotic distribution cannot be used to test the economic model's fit. To circumvent this difficulty, we propose a simple simulation method to construct critical values for the test statistics. An empirical application with US data illustrates the proposed method.     

Quest for appropriate overcapacity in the fisheries industry

The effective management of natural resources is a critical issue that concerns many people with differing interests. This paper examines aspects of overcapacity and optimal capacity within fisheries by accounting for multiple objectives. Overcapacity arises when a fishing fleet is capable of producing more than what is demanded at the industry level, or allowed by a regulatory framework. The presence of multiple objectives within fisheries management is most often an unavoidable reality, where the objectives determine what level of overcapacity is considered optimal. A two-stage model is suggested that can produce information for management in terms of tradeoffs, policy frontiers, objective values and optimal fleet structure. In the first stage, an output-based Data Envelopment Analysis (DEA) model is applied. Efficiency is evaluated and production units transformed such that they use technologically efficient inputs and produce at their full potential. In the second stage, these transformed units are included in an aggregate industry model formulated as a multi-objective optimization program. The model provides information for managers in terms of tradeoffs, policy frontiers, objective values, and optimal fleet structure (by generating Pareto optimal solutions). The proposed model has then been applied to the Danish commercial fishing fleet.     

Non-parametric estimation of sequential english auctions

I propose an empirical strategy to identify and to estimate non-parametrically the distribution and the density of latent valuations from the winning bids at sequential oral, ascending-price (hereafter English) auctions within the independent private-values paradigm. I evaluate the asymptotic and finite-sample properties of my approach, and the estimation strategy is applied to daily data from a fish auction held in Grenaa, Denmark, between January 2, 2000 and March 31, 2004.