Gabriel Rodríguez

Foreign exchange intervention and exchange rate volatility in Peru

Flexible exchange rate experience in Peru has been accompanied by frequent official interventions in the form of foreign exchange purchases or sales. Monetary authority pursues reducing excess volatility in the exchange rate through its direct intervention. However, in recent years, this intervention has concentrated on US dollar purchases, apparently signalling a bias towards defending a given exchange rate level (not necessarily fixed). For the period 1994 to 2007, this document assesses consistency of the empirical evidence with the goal of reducing exchange rate volatility. Thus, it uses univariate and multivariate time series models subject to stochastic shifts to study currency pressures. Results suggest consistency with the reduced-volatility goal. Nonetheless, in line with other studies, factors such as the foreign exchange gap with respect to its trend also induce foreign exchange intervention.

Some stylized facts of return in the foreign exchange and stock markets in Peru

Purpose - The purpose of this paper is to find and describe some stylized facts for foreign exchange and stock market returns, which are explored using statistical methods. Design/methodology/approach - Formal statistics for testing presence of autocorrelation, asymmetry, and other deviations from normality are applied. Dynamic correlations and different kernel estimations and approximations to the empirical distributions are also under scrutiny. Furthermore, dynamic analysis of mean, standard deviation, skewness and kurtosis are also performed to evaluate time-varying properties in return distributions. Findings - The findings include: different types of non-normality in both markets, fat tails, excess furtosis, return clustering and unconditional time-varying moments. Identifiable volatility cycles in both forex and stock markets are associated to common macro financial uncertainty events. Originality/value - The paper is the first work of this type in Peru.

Link between unemployment and crime in the US: a Markov-Switching approach.

This study has two goals. The first is to use Markov Switching models to identify and analyze the cycles in the unemployment rate and four different types of property-related criminal activities in the US. The second is to apply the nonparametric concordance index of Harding and Pagan (2006) to determine the correlation between the cycles of unemployment rate and property crimes. Findings show that there is a positive but insignificant relationship between the unemployment rate, burglary, larceny, and robbery. However, the unemployment rate has a significant and negative (i.e., a counter-cyclical) relationship with motor-vehicle theft. Therefore, more motor-vehicle thefts occur during economic expansions relative to contractions. Next, we divide the sample into three different subsamples to examine the consistency of the findings. The results show that the co-movements between the unemployment rate and property crimes during recession periods are much weaker, when compared with that of the normal periods of the US economy.

Persistence of Unemployment in the Canadian Provinces

The authors analyze the degree of persistence of the unemployment rates of the ten Canadian provinces using quarterly data for the period 1976:1–2005:4. They apply a two-break minimum Lagrange Multiplier (LM) unit root statistic, which, unlike standard unit root statistics (without or with breaks), makes it possible to find the stationarity of the different unemployment rates, giving support to the theory of the natural rate. The authors use the methodology of Bai and Perron (1998, 2003) to estimate a linear model with multiple structural changes to estimate the different degrees of persistence over the different regimes. The results suggest that the degree of persistence decreases when multiple breaks are allowed. Issues regarding the Canadian labor market, the insurance benefits program, interprovincial transfers, and interprovincial mobility are discussed as potential explanations for the results.

An application of a random level shifts model to the volatility of Peruvian stock and exchange rate returns

The literature has shown that the volatility of stock and forex rate market returns shows the characteristic of long memory. Another fact that is shown in the literature is that this feature may be spurious and volatility actually consists of a short memory process contaminated with random level shifts (RLS). In this paper, we follow recent econometric approaches estimating an RLS model to the logarithm of the absolute value of stock and forex returns. The model consists of the sum of a short-term memory component and a component of level shifts. The second component is specified as the cumulative sum of a process that is zero with probability ‘1-alpha’ and is a random variable with probability ‘alpha’. The results show that there are level shifts that are rare, but once they are taken into account, the characteristic or property of long memory disappears. Also, the presence of General Autoregressive Conditional Heteroscedasticity (GARCH) effects is eliminated when included or deducted level shifts. An exercise of out-of-sample forecasting shows that the RLS model has better performance than traditional models for modelling long memory such as the models ARFIMA (p,d,q).

Structural breaks and labor market disparities in the Canadian provinces

Purpose - – The purpose of this paper is to use quarterly time series data from Canada and the Canadian provinces to determine if the unemployment rates in the Canadian provinces are converging to the national rate of unemployment. Design/methodology/approach - – First, the authors check for existence of stochastic convergence using recent unit root statistics, see Perron and Rodriguez (2003) and Rodriguez (2007). Second, the authors verify existence of convergence using methods proposed by Volgelsang (1998) and Bai and Perron (1998, 2003). All these methods allows for structural break(s) in the data. Findings - – Results from different unit root tests, without and with structural breaks, confirm that stochastic convergence exists in all provinces. The other results show strong evidence that deterministic convergence exists and the unemployment rates of the Canadian provinces are converging to the unemployment rate of Canada. This conclusion is stronger when multiple breaks are allowed in the trend function using the approach of Bai and Perron (1998, 2003). Practical implications - – Since the authors have verified the existence of stochastic convergence, any intervention in the labor markets of the Canadian provinces to control the provincial unemployment rate would have a temporary effect and these policies will not have a permanent influence on the unemployment rates. However, existence of Originality/value - – To the best of the knowledge, the paper attempts to study the unemployment rate convergence in the Canadian provinces using the above-mentioned approaches. These approaches allow the authors to take into consideration the possibility of structural breaks in order to get results that are more accurate.

Stochastic Volatility in the Peruvian Stock Market and Exchange Rate Returns: A Bayesian Approximation

This study is one of the first to utilize the stochastic volatility (SV) model to modelling the Peruvian financial times series. We estimate and compare this model with generalized autoregressive conditional heteroscedasticity (GARCH) models with normal and t-student errors. The analysis in this study corresponds to Peru’s stock market and exchange rate returns. The importance of this methodology is that the adjustment of the data is better than the GARCH models, using the assumptions of normality in both models. In the case of the SV model, three Bayesian algorithms have been employed where we evaluate their respective inefficiencies in the estimation of the model’s parameters—the most efficient being the integration sampler. The estimated parameters in the SV model under the various algorithms are consistent, as they display little inefficiency. The figures of the correlations of the iterations suggest that there are no problems at the time of Markov chaining in all estimations. We find that the volatilities in the exchange rate and stock market volatilities follow similar patterns over time. That is, when economic turbulence caused by the economic circumstances occurred, for example, the Asian crisis and the recent crisis in the USA, considerable volatility was generated in both markets. JEL Classification: C22

APPLICATION OF A SHORT MEMORY MODEL WITH RANDOM LEVEL SHIFTS TO THE VOLATILITY OF LATIN AMERICAN STOCK MARKET RETURNS

Empirical research indicates that the volatility of stock return time series has long memory. However, it has been demonstrated that short memory processes contaminated by random level shifts can often be confused with long memory, a feature often referred to as spurious long memory. This paper represents an empirical study of the random level shift (RLS) model for the volatility of daily stock return data for five Latin American countries. This model consists of the sum of a short term memory component and a level shift component that is governed by a Bernoulli process with a shift probability. The results suggest that level shifts in the volatility of daily stock return data are infrequent but when taken into account, the long memory characteristic and GARCH effects disappear. An out-of-sample forecasting exercise is also provided.

A factorial decomposition of inflation in Peru: an alternative measure of core inflation

A dynamic factorial decomposition model of inflation is estimated using Peruvian monthly data for January 1995–July 2008. This model allows the identification of changes in three relevant inflation components: idiosyncratic relative prices, aggregate relative prices and absolute prices. Furthermore, following Reis and Watson (2007), the model allows measuring pure inflation as the common factor in the inflation rate that has a proportionate effect to all prices and that is not correlated with relative-price changes at any period of time. This pure inflation estimate relates closely to standard measures of core inflation. The results are robust to different lag structures and various stochastic assumptions on the estimated factors.

Selecting between Autoregressive Conditional Heteroskedasticity Models: An Empirical Application to the Volatility of Stock Returns in Peru

An extensive family of univariate models of autoregressive conditional heteroskedasticity is applied to Peru’s daily stock market returns for the period January 3, 1992 to March 30, 2012 with four different specifications related to the distribution of the disturbance term. This concerns capturing the asymmetries of the behavior of the volatility, as well as the presence of heavy tails in these time series. Using different statistical tests and different criteria, the results show that: (i) the FIGARCH (1,1)-t is the best model among all symmetric models while the FIEGARCH (1,1)-Sk is selected from the class of asymmetrical models. Also, the model FIAPARCH (1,1)-t is selected from the class of asymmetric power models; (ii) the three models capture well the behavior of the conditional volatility; (iii) however, the empirical distribution of the standardized residuals shows that the behavior of the tails is not well captured by either model; (iv) the three models suggest the presence of long memory with estimates of the fractional parameter close to the region of nonstationarity