Consumer Confidence and Yield Spreads in Europe

This paper shows the extraordinary capacity of yield spreads to anticipate consumption growth as proxy by the Economic Sentiment Indicator elaborated by the European Commission in order to predict turning points in business cycles. This new evidence complements the well known results regarding the usefulness of the slope of the term structure of interest rates to predict real economic conditions and, in particular, recessions by using a direct measure of expectations. A linear combination of European yield spreads explains a surprising 93.7% of the variability of the Economic Sentiment Indicator. Yield spreads seem to be a key determinant of consumer confidence in Europe.

Data Revisions in the Estimation of DSGE Models

Revisions of US macroeconomic data are not white-noise. They are persistent, correlated with real-time data, and with high variability (around 80% of volatility observed in US real-time data). Their business cycle effects are examined in an estimated DSGE model extended with both real-time and final data. After implementing a Bayesian estimation approach, the role of both habit formation and price indexation fall significantly in the extended model. The results show how revision shocks of both output and inflation are expansionary because they occur when real-time published data are too low and the Fed reacts by cutting interest rates. Consumption revisions, by contrast, are countercyclical as consumption habits mirror the observed reduction in real-time consumption. In turn, revisions of the three variables explain 9.3% of changes of output in its long-run variance decomposition.

An Estimated New-Keynesian Model with Unemployment as Excess Supply of Labor

Wage stickiness is incorporated to a New-Keynesian model with variable capital to drive endogenous unemployment uctuations de ned as the log di¤erence between aggregate labor supply and aggregate labor demand. We estimated such model using Bayesian econometric techniques and quarterly U.S. data. The second-moment statistics of the unemployment rate in the model give a good t to those observed in U.S. data. Our results also show that wage-push shocks, demand shifts and monetary policy shocks are the three major determinants of unemployment fl uctuations. Compared to an estimated New-Keynesian model without unemployment (Smets and Wouters, 2007): wage stickiness is higher, labor supply elasticity is lower, the slope of the New-Keynesian Phillips curve is flatter, and the importance of technology innovations on output variability increases.

Multidimensional scaling analysis of the dynamics of a country economy

This paper analyzes the Portuguese short-run business cycles over the last 150 years and presents the multidimensional scaling (MDS) for visualizing the results. The analytical and numerical assessment of this long-run perspective reveals periods with close connections between the macroeconomic variables related to government accounts equilibrium, balance of payments equilibrium, and economic growth. The MDS method is adopted for a quantitative statistical analysis. In this way, similarity clusters of several historical periods emerge in the MDS maps, namely, in identifying similarities and dissimilarities that identify periods of prosperity and crises, growth, and stagnation. Such features are major aspects of collective national achievement, to which can be associated the impact of international problems such as the World Wars, the Great Depression, or the current global financial crisis, as well as national events in the context of broad political blueprints for the Portuguese society in the rising globalization process.

Complex dynamics of financial indices

This paper presents a novel method for the analysis of nonlinear financial and economic systems. The modeling approach integrates the classical concepts of state space representation and time series regression. The analytical and numerical scheme leads to a parameter space representation that constitutes a valid alternative to represent the dynamical behavior. The results reveal that business cycles can be clearly revealed, while the noise effects common in financial indices can elegantly be filtered out of the results.

Electoral opportunism and fiscal policy before and after the EMU

A Masters Thesis, presented as part of the requirements for the award of a Research Masters Degree in Economics from NOVA – School of Business and Economics

Using a Bayesian model for bankruptcy prediction : a comparative approach

The purpose of this study is to examine the impact of the choice of cut-off points, sampling procedures, and the business cycle on the accuracy of bankruptcy prediction models. Misclassification can result in erroneous predictions leading to prohibitive costs to firms, investors and the economy. To test the impact of the choice of cut-off points and sampling procedures, three bankruptcy prediction models are assessed- Bayesian, Hazard and Mixed Logit. A salient feature of the study is that the analysis includes both parametric and nonparametric bankruptcy prediction models. A sample of firms from Lynn M. LoPucki Bankruptcy Research Database in the U. S. was used to evaluate the relative performance of the three models. The choice of a cut-off point and sampling procedures were found to affect the rankings of the various models. In general, the results indicate that the empirical cut-off point estimated from the training sample resulted in the lowest misclassification costs for all three models. Although the Hazard and Mixed Logit models resulted in lower costs of misclassification in the randomly selected samples, the Mixed Logit model did not perform as well across varying business-cycles. In general, the Hazard model has the highest predictive power. However, the higher predictive power of the Bayesian model, when the ratio of the cost of Type I errors to the cost of Type II errors is high, is relatively consistent across all sampling methods. Such an advantage of the Bayesian model may make it more attractive in the current economic environment. This study extends recent research comparing the performance of bankruptcy prediction models by identifying under what conditions a model performs better. It also allays a range of user groups, including auditors, shareholders, employees, suppliers, rating agencies, and creditors' concerns with respect to assessing failure risk.

Macroeconomic News and Exchange Rates: Evidence of Unstable Effect

Although the link between macroeconomic news announcements and exchange rates is well documented in recent literature, this connection may be unstable. By using a broad set of macroeconomic news announcements and high frequency forex data for the Euro/Dollar, Pound/Dollar and Yen/Dollar from Nov 1, 2004 to Mar 31, 2014, we obtain two major findings with regards to this instability. First, many macroeconomic news announcements exhibit unstable effects with certain patterns in foreign exchange rates. These news effects may change in magnitude and even in their sign over time, over business cycles and crises within distinctive contexts. This finding is robust because the results are obtained by applying a Two-Regime Smooth Transition Regression Model, a Breakpoints Regression Model, and an Efficient Test of Parameter Instability which are all consistent with each other. Second, when we explore the source of this instability, we find that global risks and the reaction by central bank monetary policy to these risks to be possible factors causing this instability.

Macroeconomic News Effects and Foreign Exchange Jumps

This thesis investigates how macroeconomic news announcements affect jumps and cojumps in foreign exchange markets, especially under different business cycles. We use 5-min interval from high frequency data on Euro/Dollar, Pound/Dollar and Yen/Dollar from Nov. 1, 2004 to Feb. 28, 2015. The jump detection method was proposed by Andersen et al. (2007c), Lee & Mykland (2008) and then modified by Boudt et al. (2011a) for robustness. Then we apply the two-regime smooth transition regression model of Teräsvirta (1994) to explore news effects under different business cycles. We find that scheduled news related to employment, real activity, forward expectations, monetary policy, current account, price and consumption influences forex jumps, but only FOMC Rate Decisions has consistent effects on cojumps. Speeches given by major central bank officials near a crisis also significantly affect jumps and cojumps. However, the impacts of some macroeconomic news are not the same under different economic states.

The Compliance Costs of Taxes on Businesses and Individuals a Review of the Evidence

This Paper Reviews the Literature on the Compliance Costs Incurred by Businesses and Individuals Because of One Or More Taxes. It Presents Both the Main Characteristics, Such As Sample Size, Interview Techniques and So On, and the Key Findings of the Nineteen Studies Reviewed. in General, One Can Conclude That Simpler Taxes Lead to Lower Compliance Costs.

Why Have Aggregate Skilled Hours Become So Cyclical Since the Mid-1980's?

This paper documents and discusses a dramatic change in the cyclical behavior of aggregate hours worked by individuals with a college degree (skilled workers) since the mid-1980’s. Using the CPS outgoing rotation data set for the period 1979:1-2003:4, we find that the volatility of aggregate skilled hours relative to the volatility of GDP has nearly tripled since 1984. In contrast, the cyclical properties of unskilled hours have remained essentially unchanged. We evaluate the extent to which a simple supply/demand model for skilled and unskilled labor with capital-skill complementarity in production can help explain this stylized fact. Within this framework, we identify three effects which would lead to an increase in the relative volatility of skilled hours: (i) a reduction in the degree of capital-skill complementarity, (ii) a reduction in the absolute volatility of GDP (and unskilled hours), and (iii) an increase in the level of capital equipment relative to skilled labor. We provide empirical evidence in support of each of these effects. Our conclusion is that these three mechanisms can jointly explain about sixty percent of the observed increase in the relative volatility of skilled labor. The reduction in the degree of capital-skill complementarity contributes the most to this result.

The Effect of Public Spending on Consumption: Reconciling Theory and Evidence

Recent empirical evidence from vector autoregressions (VARs) suggests that public spending shocks increase (crowd in) private consumption. Standard general equilibrium models predict the opposite. We show that a standard real business cycle (RBC) model in which public spending is chosen optimally can rationalize the crowding-in effect documented in the VAR literature. When such a model is used as a data-generating process, a VAR estimated using the artificial data yields a positive consumption response to an increase in public spending, consistent with the empirical findings. This result holds regardless of whether private and public purchases are complements or substitutes.

Estimating Nonlinear DSGE Models by the Simulated Method of Moments

This paper studies the application of the simulated method of moments (SMM) for the estimation of nonlinear dynamic stochastic general equilibrium (DSGE) models. Monte Carlo analysis is employed to examine the small-sample properties of SMM in specifications with different curvature. Results show that SMM is computationally efficient and delivers accurate estimates, even when the simulated series are relatively short. However, asymptotic standard errors tend to overstate the actual variability of the estimates and, consequently, statistical inference is conservative. A simple strategy to incorporate priors in a method of moments context is proposed. An empirical application to the macroeconomic effects of rare events indicates that negatively skewed productivity shocks induce agents to accumulate additional capital and can endogenously generate asymmetric business cycles.

Caracterización de la utilización de innovación en el sector bancario: Una aproximación hacia la adquisición de ventajas competitivas

Investigación exploratoria mixta siguiendo un método deductivo con la que se logró caracterizar el grado de utilización de innovación en el sector bancario y su utilidad en la adquisición de ventajas competitivas con la ayuda de del modelo del Radar de Innovación.

Estado situacional de los modelos basados en agentes y su impacto en la investigación organizacional

En un mundo hiperconectado, dinámico y cargado de incertidumbre como el actual, los métodos y modelos analíticos convencionales están mostrando sus limitaciones. Las organizaciones requieren, por tanto, herramientas útiles que empleen tecnología de información y modelos de simulación computacional como mecanismos para la toma de decisiones y la resolución de problemas. Una de las más recientes, potentes y prometedoras es el modelamiento y la simulación basados en agentes (MSBA). Muchas organizaciones, incluidas empresas consultoras, emplean esta técnica para comprender fenómenos, hacer evaluación de estrategias y resolver problemas de diversa índole. Pese a ello, no existe (hasta donde conocemos) un estado situacional acerca del MSBA y su aplicación a la investigación organizacional. Cabe anotar, además, que por su novedad no es un tema suficientemente difundido y trabajado en Latinoamérica. En consecuencia, este proyecto pretende elaborar un estado situacional sobre el MSBA y su impacto sobre la investigación organizacional.