Structural breaks and switching processes are known to induce apparent long memory in a time series. Here we show that any significant time variation in the mean renders the sample correlogram (and related spectral estimates) inconsistent. In particular, smooth time variation in the mean—i.e., even a weak trend, either stochastic or deterministic—induces apparent long memory. This apparent long memory can be eliminated by either high-pass filtering or by detrending. Here we demonstrate the effectiveness in this regard of nonlinear detrending via penalized-spline nonparametric regression. A time-varying mean can be of economic interest in its own right. This suggests that isolating out and separately examining both a local mean (i.e., a nonlinear trend or the realization of a stochastic trend) and deviations from it is preferable as a modeling strategy to simply estimating a fractionally integrated model. We illustrate the superiority of this strategy using stock return volatility data.

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.

Specification tests reject a linear inflation forecasting model over the period 1959–2002. Based on this finding, we evaluate the out-of-sample inflation forecasts of a fully nonparametric model for 1994–2002. Our two main results are that: (i) nonlinear models produce much better forecasts than linear models, and (ii) including money growth in the nonparametric model yields marginal improvements, but including velocity reduces the mean squared forecast error by as much as 40%. A threshold model fits the data well over the full sample, offering an interpretation of our findings. We conclude that it is important to account for both nonlinearity and the behavior of monetary aggregates when forecasting inflation.

Within the seminal asset-pricing model by Brock and Hommes (Journal of Economic Dynamics Control 22, 1235–1274, 1998), heterogeneous boundedly rational agents choose between a fixed number of expectation rules to forecast asset prices. However, agents’ heterogeneity is limited in the sense that they typically switch between a representative technical and a representative fundamental expectation rule. Here, we generalize their framework by considering that all agents follow their own time-varying technical and fundamental expectation rules. Estimating our model using the method of simulated moments reveals that it is able to explain the statistical properties of the daily and monthly behavior of the S&P500 quite well. Moreover, our analysis reveals that heterogeneity is not only a realistic model property but clearly helps to explain the intricate dynamics of financial markets.

We construct a growth model with status preference to explore the effects of patents on innovation and social welfare. We find a nonmonotonic effect of patent protection on innovation. Additionally, the growth-rate-maximizing degree of patent protection decreases when the strength of status preference is larger. The effect of patent protection on social welfare is ambiguous, depending on the strength of status preference. Moreover, wealth inequality widens as patent protection is reinforced. Finally, by using cross-section regression analysis, we document that a nonmonotonic relationship between patent protection and economic growth is statistically significant and that the growth-rate-maximizing degree of patent protection decreases with the strength of status preference.

The nonlinearity of macroeconomic processes is becoming an increasingly important issue at both the theoretical and empirical levels. This trend holds for labor market variables as well. The reallocation theory of unemployment relies on nonlinearities. At the same time there is mounting empirical evidence of business cycles asymmetries. Thus the assumption of linearity/nonlinearity becomes crucial for the corroboration of labor market theories. This paper turns the microscope on the assumption of linearity and investigates the presence of asymmetries in aggregate and disaggregate labor market variables. The assumption of linearity is tested using five statistical tests for U.S. and Canadian unemployment rates and growth rates of the employment sectoral shares of construction, finance, manufacturing, and trade. An AR(p) model was used to remove any linear structure from the series. Evidence of nonlinearity is found for the sectoral shares with all five statistical tests in the U.S. case but not at the aggregate level. The results for Canada are not clear-cut. Evidence of unspecified nonlinearity is found in the unemployment rate and in the sectoral shares. Overall, important asymmetries are found in disaggregated labor market variables in the univariate setting. The linearity hypothesis was also examined in a multivariate framework. Evidence is provided that important asymmetries exist and a linear VAR cannot capture the dynamics of employment reallocation.

Recent literature on the design of optimal monetary policy has shown that deviations from price stability are small whenever prices are sticky. This paper reconsiders this issue by introducing capital accumulation in the model. Optimal monetary policy in this setup implies small deviations from price stability. The monetary authority optimally uses inflation as an explicit tax on monopolistic profits to reduce the price markup across states. Variable markup is achieved in this setup because the share of investment demand over output varies across states and in response to TFP shocks.

We analyze the impact of financial globalization on volatilities of hours worked and wages of high-skilled and low-skilled workers. Using cross-country, industry-level data for the years 1970–2004, we establish stylized facts that document how volatilities of hours worked and wages of workers with different skill levels have changed over time. We then document that the volatility of hours worked by low-skilled workers has increased the most in response to the increase in financial globalization. We develop a dynamic stochastic general equilibrium model of a small open economy that is consistent with the empirical results. The model predicts that greater financial globalization increases the volatility of hours worked, and this effect is strongest for low-skilled workers.

We study the impacts of investment in public capital on equity and efficiency. Taking into account stylized facts on wealth accumulation, we model agent heterogeneity through differences in saving behavior, income source and time preference. We find that in the long run, public investment is Pareto-improving and that it reduces inequality in wealth, welfare, and income at the same time, if it is financed by a capital tax. Consumption tax financing is also Pareto-improving but distribution-neutral. Only for labor tax financing, a trade-off between equity and efficiency occurs. Additionally, we find that agents differ in their preferred tax rates.The results for capital and labor tax financing are valid for both, the case of decreasing and constant returns to accumulable factors.

Since 1900, annual working hours per worker have been generally declining in the United States and in the main European economies. During this simultaneous decline the Europeans initially worked fewer hours than their American counterparts, worked more than the Americans starting in the early 1930s, and once again worked less than the American from the early 1970s on. Using a two-country model, this article argues that this dynamic pattern can be brought about by differences in the valuation of leisure by individuals in the compared economies.

We develop a dynamic partial equilibrium model of the housing market, in which the dynamics of the house price is determined by the interaction between chartists and fundamentalists. The model endogenously generates episodes of boom and bust in the house price and can replicate the recent US house price dynamics, and points to endogenous and exogenous behavioral factors as the main determinants of such dynamics.

We revisit the sources of the bias in Federal Reserve forecasts and assess whether a precautionary motive can explain the forecast bias. In contrast to the existing literature, we use forecasts submitted by individual Federal Open Market Committee (FOMC) members to uncover members' implicit loss function. Our key finding is that the loss function of FOMC members is asymmetric: FOMC members incur a higher loss when they underpredict (overpredict) inflation and unemployment (nominal and real growth) as compared to their making an overprediction (underprediction) of similar size. We also find that an asymmetric loss function, in some cases, weakens evidence against forecast rationality, though results depend on the variable being projected and the subgroup of FOMC members being studied. Furthermore, we add to the recent controversy on the relative quality of FOMC forecasts compared to staff forecasts. Our results suggest that differences in predictive ability could indeed stem from differences in preferences.

We estimate a two-country open economy version of the New Keynesian dynamic stochastic general equilibrium model for the United States and the Euro area, using Bayesian techniques that allow for both determinacy and indeterminacy of the equilibrium. Empirical analysis shows that the worldwide equilibrium is indeterminate due to a passive monetary policy in the Euro area, even if U.S. policy is aggressive enough. We demonstrate that the impulse responses under indeterminacy exhibit dynamics different from those under determinacy and that sunspot shocks affect the Euro economy to a substantial degree, whereas the transmission of sunspots to the United States is limited.

The convergence hypothesis, which is developed in the context of growth economics, asserts that the income differences across countries are transitory, and developing countries will eventually attain the level of income of developed ones. On the other hand, convergence clubs hypothesis claim that the convergence can only be realized across groups of countries that share some common characteristics. In this study, we propose a new method to find convergence clubs that combines a pairwise method of testing convergence with maximum clique and maximal clique algorithms. Unlike many of those already developed in the literature, this new method aims to find convergence clubs endogenously without depending on a-priori classifications. In a Monte Carlo simulation study, the success of the method in finding convergence clubs is compared with a similar algorithm. Simulation results indicated that the proposed method perform better than the compared algorithm in most cases. In addition to the Monte Carlo, a new empirical evidence on the existence of convergence clubs is presented in the context of real data applications.

I develop a dynamic political economy model with an informal sector and two political parties alternating in office. In equilibrium, if the incumbent political party faces a higher probability of staying in office, it sets a higher tax rate on the formal economy to invest more in productive public capital, while spending less for current office rent. Moreover, I argue that public capital is mainly utilized by the formal sector, and this implies that countries in which incumbent parties are more likely to stay in power have a higher tax burden but a smaller informal sector. I also present some empirical evidence that supports the main results of the model.

In this paper, we reconsider the theoretical basis for the Lucas critique from the point of view of robust decision theory. We first emphasize that the Lucas critique rests on a weak theoretical paradigm in that it fails to consider the motivation for the policy change by the government and hence inconsistently assumes limited rationality by the government. When placed in a proper dynamic general equilibrium framework of a dynamic game between the government and the private sector, much of the force of the critique simply vanishes. We also reconsider the critique by adopting an alternative theoretical paradigm and notion of rationality based on robust decision theory. This view of rationality might be regarded as more relevant than the nonrobust rationality employed by Lucas and, critically, it is one in which the Lucas critique can be shown simply not to apply, provided the private sector has adopted suitably robust decision rules.

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.

Dynamic models in which agents' behavior depends on expectations of future prices or other endogenous variables can have steady states that are stationary equilibria for a wide variety of expectations rules, including rational expectations. When there are multiple steady states, stability is a criterion for selecting among them as predictions of long-run outcomes. The purpose of this paper is to study how sensitive stability is to certain details of the expectations rules, in a simple OLG model with constant government debt that is financed through seigniorage. We compare simple recursive learning rules, learning rules with vanishing gain, and OLS learning, and also relate these to expectational stability. One finding is that two adaptive expectation rules that differ only in whether they use current information can have opposite stability properties.

This paper tries to infer and compare the evolution of the Federal Reserve’s (unobserved) inflation target series by estimating a monetary model under the alternative assumptions of rational expectations or subjective expectations and learning. In the estimated model that assumes that economic agents have rational expectations, the implied inflation target displays large shifts over time: it starts at 2% in the early 1960s, it rises to 8% in the 1970s, and it falls to 4% and 2% in the 1980s and 1990s. When the assumption of rational expectations is relaxed in favor of learning by the policymaker, the inferred target is, instead, remarkably stable over time. The target assumes values between 2% and 3% over the whole postwar sample. The findings suggest changing beliefs and learning by the Federal Reserve as major endogenous causes of the perceived variation in the inflation target. When the model is allowed to take the central bank’s evolving beliefs into account, the joint evolution of US inflation, output, and monetary policy decisions can be explained without requiring large exogenous changes in the inflation target.

We analyze the importance of the frequency of decision making for macroeconomic dynamics, in the context of a simple, well-known business cycle model with balanced budget rules. We explain how the frequency of decision making (period length) and the measurement unit of time (calibration frequency) differ and examine how local stability is affected by changes in the period length. We find that as the period grows longer, indeterminacy occurs less often. This may have significant quantitative implications: for the model at hand, there is a wide range of economically relevant labor tax rates (from 30% to 38%) for which the continuous-time model gives indeterminacy, whereas the discrete-time model has determinate dynamics.