INFLACIÓN E INCERTIDUMBRE INFLACIONARIA: EVIDENCIA PARA COSTA RICA

En este documento se estima una medida de la incertidumbre inflacionaria. Un modelo de inflación señala incertidumbre cuando los errores de pronóstico son heteroscedásticos. Por medio de la especificación de una ecuación GARCH (Generalized Autoregressive Conditional Heteroscedasticity), para la varianza del término de error de un modelo de inflación, es posible estimar una proxy de incertidumbre inflacionaria. La estimación simultánea del modelo de inflación y de la ecuación GARCH, produce un nuevo modelo de inflación en el cual los errores de pronóstico son homocedásticos. Existe consenso en la literatura económica en que hay una correlación positiva entre incertidumbre inflacionaria y la magnitud de la tasa de inflación, lo cual, como lo señaló Friedman (1977), representa uno de los costos asociados con la persistencia inflacionaria. Esto es porque tal incertidumbre dificulta la toma de decisiones óptimas por parte de los agentes económicos.La evidencia empírica, para el periodo 1954:01-2002:08, apoya la hipótesis de que para el caso de Costa Rica mientras mayor es la inflación mayor es la incertidumbre respecto a esta variable. En los últimos siete años (1997-2002) la incertidumbre presenta la variación media más baja de todo el periodo. Además, se identifica un efecto asimétrico de la inflación sobre la incertidumbre inflacionaria, es decir, la incertidumbre inflacionaria tiende a incrementarse más para el siguiente periodo cuando la inflación pronosticada está por debajo de la inflación actual, que cuando la inflación pronosticada está por arriba de la tasa observada de inflación. Estos resultados tienen una clara implicación para la política monetaria. Para minimizar la dificultad que la inflación causa en la toma óptima de decisiones de los agentes económicos es necesario perseguir no solamente un nivel bajo de inflación sino que también sea estable.AbstractThis paper estimates a measure of inflationary uncertainty. An inflation model signals uncertainty when the forecast errors are heteroskedastic. By the specification of a GARCH (Generalized Autoregressive Conditional Heteroscedasticity) equation, for the variance of the error term of the inflation model, it is possible to estimate a proxy for inflationary uncertainty. By the simultaneous estimation of the inflation model and the GARCH equation, a new inflation model is obtained in which the forecast errors are homocedastic. Most economists agree that there is a positive correlation between inflationary uncertainty and the magnitude of the inflation rate, which, as was pointed out by Friedman (1977), represents one of costs associated with the persistence of inflation. This is because such uncertainty clouds the decision-making process of consumers and investors.The empirical evidence for the period 1954:01-2002:08 confirms that in the case of Costa Rica inflationary uncertainty increases as inflation rises. In the last seven years(1997-2002) the uncertainty present the mean variation most small of the period. In addition, inflation has an asymmetric effect on inflationary uncertainty. That is, when the inflation forecast is below the actual inflation, inflationary uncertainty increases for the next period. The opposite happens when the inflation forecast is above the observed rate of inflation. Besides, the absolute value of the change on uncertainty is greater in the first case than the second. These results have a clear implication for monetary policy. To minimize the disruptions that inflation causes to the economic decision-making process, it is necessary to pursue, not only a low level of inflation, but a stable one as well.

Technical performance profile of the four-time Costa Rican senior basketball league championship team

The purpose of this study was to analyze and compare the technical performance profile of the four-time Costa Rican Senior Basketball League championship team. A total of 142 games was recorded throughout the 2007, 2008 and 2009 seasons. Performance indicators selected were: two and three-point shots (converted, missed, effectiveness rates), free throws (converted, missed, effectiveness rates), points, offensive and defensive rebounds, fouls, turnovers, assists and ball steals. The information was described based on absolute and relative frequency values. Data was compared by season and by playing period based on the following non-parametric techniques: U-test, Friedman test and Chi-square. In all cases, SPSS version 15.0 was used with a significance level of p ≤ 0.05. Results showed a better profile of technical performance in the 2008 season, characterized by better percentages of two-point shots, free throws, fewer turnovers and more ball steals and assists. In relation to the playing period, the team showed a better technical performance profile during the second half of the matches. In general, the effectiveness rate of two-point shots and free throws was above 60% in both playing periods, while the three-point shot percentage ranged between 26.4% and 29.2%. In conclusion, the team showed a similar technical performance profile to that reported in the literature, as well as a clear evidence of the importance of recording and following up on technical performance indicators in basketball.