We estimate a medium-scale dynamic stochastic general equilibrium (DSGE) model for the euro area in an open-economy framework. The model includes structural trends on all variables, allowing us to estimate on gross data. First, we provide a theoretical balanced growth path consistent with permanent productivity shocks, inflation target changes, and permanent shocks to the openness of the economies. We then define the cycle as the gap between this sustainable trajectory and the gross data. Hence, we can properly deal with persistent deviations of the trade balance. Finally, we find persistent and strong effects from the asymmetric increase of euro-area imports during the last 10 years on domestic inflation. From 2000Q1 to 2008Q4, we estimate the contribution of the imbalanced development of international trade on euro-area inflation to an average of −0.7%, and on nominal interest rate, to an average of −1.4%.

This paper reconsiders optimal inflation targeting in a model where persistence is generated by rational choices of the price makers because of a time-dependent pricing mechanism. In this framework, which generalizes the traditional Calvo model, inflation persistence is intrinsic, as it is micro-founded assuming that firms' pricing decisions depend on the time elapsed from the last price reset. We use a linear–quadratic approach to study the welfare effects and optimal policies. We disentangled two distortion sources showing how welfare falls in both the average of the probability of changing prices and its distribution among different firms. Described the underlying distortions of our setup, we analyze its normative implications for optimal inflation. The issues of uncertainty and robustness are also considered: By using robust control techniques, we, in fact, consider the consequences of implementing a “wrong” monetary rule due to a misinterpretation of sources of inflation inertia.

I study the role of shocks to beliefs combined with Bayesian learning in a standard equilibrium business cycle framework. In particular, I examine how a prior belief arising from the Great Depression may have influenced the macroeconomy during the last 75 years. In the model, households hold twisted beliefs concerning the likelihood and persistence of recession and boom states that are affected by the Great Depression. These initial beliefs are substantially different from the true data generating process and are only gradually unwound during subsequent years. Even though the driving stochastic process for technology is unchanged over the entire period, the nature of macroeconomic performance is altered considerably for many decades before eventually converging to the rational expectations equilibrium. This provides some evidence of the lingering effects of beliefs-twisting events on the behavior of macroeconomic variables.

This study investigates the determinants of the fertility transition in the United States from 1850 to the end of the 20th century. We find a robust negative relation between years of schooling and fertility. The magnitude of our baseline estimate suggests that the rise in schooling accounts for about 60% of the US fertility decline. In contrast, we find no evidence of a robust relation between income per capita and fertility. This pattern corroborates theories stressing the importance of human capital investments in generating a transition from high to low fertility.

A general equilibrium model with financial frictions in which individuals may encounter unobservable investment opportunities is developed along the lines of Kiyotaki and Moore (2012). I study efficiency properties induced by money and monetary policy when financial frictions prevent optimal equilibrium allocations. By providing closed-form solutions to all prices, allocations, welfare, and, especially, the distribution of individuals with respect to assets, I show that the Friedman rule achieves maximal social welfare, independent of how tight the financial constraints may be. The same level of welfare would be induced by an omniscient central planner able to verify who has an investment opportunity.

I examine the optimal inflation target in a dynamic stochastic New Keynesian model featuring an occasionally binding zero lower bound on nominal interest rate (ZLB). To this end, I first calibrate the shock needed to generate the risk of hitting the ZLB that matches the U.S. data, based on a fully nonlinear method. I then resolve the model with different inflation targets and find that the optimal target is 3.4%. In addition, the optimal inflation target is a nonlinear function of the risk of hitting the ZLB and inflation indexation. It is always greater than 2% if the risk is greater than 2.5% or if the inflation indexation is higher than 0.5. Finally, the linear–quadratic approach overestimates the true optimal inflation target. In particular, based on the benchmark calibration, it generates an optimal target of 5.5%, compared with 3.4% found by the fully nonlinear method.

We study the impact of oil price shocks on the U.S. stock market volatility. We jointly analyze three different structural oil market shocks (i.e., aggregate demand, oil supply, and oil-specific demand shocks) and stock market volatility using a structural vector autoregressive model. Identification is achieved by assuming that the price of crude oil reacts to stock market volatility only with delay. This implies that innovations to the price of crude oil are not strictly exogenous, but predetermined with respect to the stock market. We show that volatility responds significantly to oil price shocks caused by unexpected changes in aggregate and oil-specific demand, whereas the impact of supply-side shocks is negligible.

We employ a non-recursive identification scheme to identify the effects of a monetary policy shock in a Structural Vector Autoregressive (SVAR) model for the US post-WWII quarterly data. The identification of the shock is achieved via heteroskedasticity, and different on-impact macroeconomic responses are allowed for (but not imposed) in each volatility regime. We show that the impulse responses obtained with the suggested non-recursive identification scheme are quite similar to those conditional on a recursive VAR estimated with pre-1984 data. In contrast, recursive vs. non-recursive identification schemes return different short-run responses of output and investment during the Great Moderation. Robustness checks dealing with a different definition of investment, an alternative break-point, and federal funds futures rates as an indicator of the monetary policy stance are documented and discussed.

It is commonly accepted that credit market frictions are an important source of macroeconomic fluctuations. But what is the link between the two? And what is the driving factor of asset prices volatility? To answer these questions, we have introduced a specific credit friction, limited commitment, in a general equilibrium model with production and investment in productive capital, where agents can trade bonds. The model always displays a stationary equilibrium where bonds are traded. More importantly, limited commitment may generate stochastic endogenous fluctuations driven by self-fulfilling volatile expectations (sunspots), yielding credit and investment cycles and bond price volatility consistent with data.

We consider a New-Keynesian model with financial and labor market frictions where firms borrowing is limited by the enforcement constraint. The wage is set in a bargaining process where the firm's shareholder and worker share the production surplus. As debt service is considered to be a part of production costs, firms borrow to reduce the surplus which allows to lower the wage. We study the model's response to financial shock under two Taylor-type interest rate rules: first one responds to inflation and borrowing, second one to inflation and unemployment. We have found that the second rule delivers better policy in terms of the welfare measure. Additionally, we show that the feedback on unemployment in this rule depends on the extent of workers' bargaining power.

This paper argues that the marked reduction in the burden of parasitic and infectious diseases (PID) together with improved nutrition over the past two centuries in today's advanced countries has resulted in markedly improved physiological capital and cognitive skills and, consequently, in productivity advances. Using a unique annual dataset covering the period 1800–2011 for 21 OECD (Organisation for Economic Co-operation and Development) countries, it is found that health improvements can account for approximately a third of the productivity advances in the OECD countries since 1865, and that these improvements have been influential for enhancement in education, savings, innovations, life expectancy, and democracy.

We consider a DSGE model with monopolistically competitive banks together with endogenous firms' entry. We find that our model implies higher volatilities of both real and financial variables than those implied by a dynamic stochastic general equilibrium (DSGE) model with a monopolistic banking sector and a fixed number of firms. The response of the economic activity is also more persistent in response to all shocks. Furthermore, we show that inefficient banks enhance the endogenous propagation of the shocks with respect to a model where banks compete under perfect competition and can fully ensure against the risk of firms' default.

This paper presents a theoretical and empirical investigation of the relationship between human capital composition and economic growth. In the theoretical analysis, we allow for nonconstant returns to scale in technological activities. Differently from previous literature, our results show that, under broad and plausible model parameterizations, the marginal growth effect of skilled workers is increasing with the distance to the frontier for sufficiently poor countries while it is decreasing (in agreement with the existing literature) only for countries close to the technological frontier. Our empirical analysis provides robust evidence for this theoretical prediction by using a 10-year panel of 85 countries for the years in between 1960 and 2000, as well as by using the System Generalized Methods of Moments (GMM) technique to address the problem of endogeneity. Results are robust to different proxies of human capital and different specifications.

When the returns to scale of a production process vary with the intensity it is operated at, an AK model with constant returns to scale in production arises endogenously due to replication driven by profit maximization. If replication occurs at the efficiency-maximizing scale, as with perfect competition, the result applies also when the number of production processes must be discrete, thus, overcoming the so-called integer problem. When competition is imperfect, there is only convergence toward the AK model for large enough input use, so an economy is more prone to stalling in a steady state without growth, the smaller and less competitive it is.

This paper emphasizes the use of data-driven techniques to discern trends in commodity prices. Whereas many previous papers rely on parametric assumptions, we take as our departure point the view that such trends are inherently nonparametric, driven by complex forces of innovation and obsolescence, competition and strategic behavior, resource depletion and discovery, and supply and demand. Our reference specification is the partial linear model yt = f(t) + ztβ + ϵt where macroeconomic variables z enter parametrically, and f is nonparametric, to be discovered using cross-validation.

We analyze data on 11 commodities—3 hydrocarbons and 8 metals. For the majority of these commodities, our data-driven estimates of f bear close similarity to band pass estimates which include long term trends and super cycles. The OPEC effect is estimated to have increased oil prices by over 50% on average and coal prices by about 25%. U.S. coal mining legislation is estimated to have increased coal prices by 9% to 15%.

We document the strong evidence of time variation in the volatility of Euro Area business cycles since 1970. Then we provide the quantitative sources of these changes using a medium-scale DSGE model allowing time variation in structural disturbance variances. We show that (1) the size of different types of shock oscillates, in a synchronized manner, between two regimes over time, with the high-volatility regime prevailing predominantly in the 1970s, sporadically in the 1980s and 1990s, and during the Great Recession; (2) their relative importance remains, however, unchanged across regimes, where neutral technology shocks and marginal efficiency of investment shocks are the dominant sources of business cycle fluctuations; and 3) these investment shocks, which affect the transformation of savings into productive capital, can be interpreted as an indicator of credit conditions.

Current Population Survey (CPS) data over the period from 1994 to 2008 show that inflation has a positive effect on the residual wage dispersion. To explain this phenomenon, we introduce uncoordinated job searches into a general equilibrium monetary search framework. Our model shows that the uncoordinated job searches by unemployed workers give rise to an equilibrium, where a firm is matched with zero, one, or multiple job applicants. The ex post difference in matching probabilities generates a two-point wage dispersion among identical workers, when the Mortensen rule is implemented in the wage-determination process. In our model, inflation positively influences the wage dispersion directly through its impact on firm's real profit and indirectly through the effect of inflation that spills over from the goods market to the labor market. With reasonable parameter values, the calibrated model can account for most of the observed responses of residual wage dispersion to inflation.

Recent research has shown that forward-looking Taylor rules are subject to indeterminacy in New Keynesian models with capital and investment spending. This paper shows that adopting a forward-looking Wicksellian rule that responds to the price level, rather than to inflation, is one potential remedy for the indeterminacy problem. This result is shown to be robust to variations in both the labor supply elasticity and the degree of price stickiness, the inclusion of capital adjustments costs, and if output also enters into the interest-rate feedback rule. Finally, it is shown that the superiority of Wicksellian rules over Taylor rules is not only confined to forward-looking policy, but also extends to both backward-looking and contemporaneous-looking specifications of the monetary policy rule.

This paper studies stock price comovements in two key regions [the United States and Europe, which is represented by three major European developed countries (France, Germany, and the United Kingdom)]. Our paper uses recent high-frequency data (HFD) and investigates price comovements in the context of “normal times” and crisis periods. To this end, we applied a non-Gaussian Asymmetrical Dynamic Conditional Correlation (ADCC)-GARCH (Generalized Autoregressive Conditional Heteroscedasticity) model and the Marginal Expected Shortfall (MES) approach. This choice has three advantages: (i) With the development of high-frequency trading (HFT), it is more appropriate to use HFD to test price linkages for overlapping and nonoverlapping data. (ii) The ADCC-GARCH model captures further asymmetry in price comovements. (iii) The use of the MES enables to measure systemic risk contributions around the distribution tails. Accordingly, we offer two interesting findings. First, while the hypothesis of asymmetrical and time-varying stock return linkages is not rejected, the MES approach indicates that both European and US indices make a considerable contribution to each other's systemic risk, with significant input from Frankfurt to the French and US markets, especially following the collapse of Lehman Brothers. Second, we show that the propagation of systemic risk is higher during the crisis period and overlapping trading hours than during nonoverlapping hours. Thus, the MES test is recommended as an indicator to help monitor market exposure to systemic risk and to gauge expected losses for other markets.