Short run and long run causality in time series: Inference

We propose methods for testing hypotheses of non-causality at various horizons, as defined in Dufour and Renault (1998, Econometrica). We study in detail the case of VAR models and we propose linear methods based on running vector autoregressions at different horizons. While the hypotheses considered are nonlinear, the proposed methods only require linear regression techniques as well as standard Gaussian asymptotic distributional theory. Bootstrap procedures are also considered. For the case of integrated processes, we propose extended regression methods that avoid nonstandard asymptotics. The methods are applied to a VAR model of the U.S. economy.

Yesterday’s Games: Contingency Learning and the Growth of Public Spending, 1890-1938

Neither democracy nor globalization can explain the doubling of the peacetime public share in many Western countries between World Wars I and II. Here we examine two other explanations that are consistent with the timing of the observed changes, namely, (1) a shift in the demand for public goods and (2) the effect of war on the willingness to share. We first model each of these approaches as a contingency-learning phenomenon within Schelling’s Multi-Person Dilemma. We then derive verifiable propositions from each hypothesis. National time series of public spending as a share of GNP reveal no unit root but a break in trend, a result shown to favor explanation (2) over (1).

Monte Carlo Tests with Nuisance Parameters: A General Approach to Finite-Sample Inference and Nonstandard Asymptotics

The technique of Monte Carlo (MC) tests [Dwass (1957), Barnard (1963)] provides an attractive method of building exact tests from statistics whose finite sample distribution is intractable but can be simulated (provided it does not involve nuisance parameters). We extend this method in two ways: first, by allowing for MC tests based on exchangeable possibly discrete test statistics; second, by generalizing the method to statistics whose null distributions involve nuisance parameters (maximized MC tests, MMC). Simplified asymptotically justified versions of the MMC method are also proposed and it is shown that they provide a simple way of improving standard asymptotics and dealing with nonstandard asymptotics (e.g., unit root asymptotics). Parametric bootstrap tests may be interpreted as a simplified version of the MMC method (without the general validity properties of the latter).

An Autoregressive Spectral Density Estimator at Frequency Zero for Nonstationarity Tests.

Many unit root and cointegration tests require an estimate of the spectral density function at frequency zero at some process. Kernel estimators based on weighted sums of autocovariances constructed using estimated residuals from an AR(1) regression are commonly used. However, it is known that with substantially correlated errors, the OLS estimate of the AR(1) parameter is severely biased. in this paper, we first show that this least squares bias induces a significant increase in the bias and mean-squared error of kernel-based estimators.

Do Inflation-Targeting Central Banks Implicitly Target the Price Level?

This paper reports graphical and statistical evidence that the inflation targeting regimes in Canada and the UK - but not in Australia, New Zealand, or Sweden - actually resemble price-level targeting. In particular, the price level closely tracks the path implied by the inflation target, and the time-series predictions of the "bygones-are-bygones" version of inflation targeting are rejected by the data in favor of those implied by price-level targeting. These results indicate heterogeneity in the actual application of inflation targeting across countries and, for Canada and the UK, imply that the characterization of inflation targeting as a policy where shocks are accommodated is at odds with the data. Moreover, up to extent that their current policies already resemble price-level targeting, the welfare gains of replacing inflation with (explicit) price-level targeting are likely to be small.

Sostenibilidad fiscal: una aproximación con datos panel para 8 países Latinoaméricanos

Este documento examina la hipótesis de sostenibilidad fiscal para 8 países de Latinoamérica. A partir de un modelo de datos panel, se determina si los ingresos y gasto primario de los Gobiernos entre 1960 - 2009 están cointegrados, es decir, si son sostenibles a largo plazo. Para esto, se utilizaron pruebas de raíz unitaria y cointegración de segunda generación con datos panel macroeconómicos, lo que permite tener en cuenta la dependencia cruzada entre los países, así como los posibles quiebres estructurales en la relación que estén determinados de manera endógena; en particular, se usan la prueba de estacionariedad de Hadri y Rao (2008) y la prueba de cointegración de Westerlund (2006). Como resultado del análisis se encontró evidencia empírica de que en el período bajo estudio el déficit primario en los 8 países latinoamericanos es sostenible pero en sentido débil.

An analysis of the relationship between wages in the public and private sector in colombia : a panel data approach

This document examines the time-series properties of the wage differentials that arise between the public and private sector in Colombia during the sample period 1984 to 2005. We Find conflicting results in unit-root and stationary tests when looking at wage differentials at an aggregate level (such as for men, women or both). However, when we analyse wage differentials at higher levels of disaggregation, treat them jointly as a panel of data, and allow for the presence of potential cross section dependence, there is more supportive evidence for the view that wage differentials are stationary. This implies that although wage differentials do exist, they have not been consistently increasing (or decreasing) over time.

Seasonal adjustment and cointegration

El documento examina el efecto de filtros de ajuste en el tamaño y poder de prueba de cointegración que usan los residuales como pruebas ADF y PP, mediante procedimientos MonteCarlo y una aplicación empírica. Nuestros resultados indican que el uso de filtros distorsiona el tamaño y reduce el poder de estas pruebas.

Bayesian model averaging and identification of structural breaks in time series

Bayesian Model Averaging (BMA) is used for testing for multiple break points in univariate series using conjugate normal-gamma priors. This approach can test for the number of structural breaks and produce posterior probabilities for a break at each point in time. Results are averaged over specifications including: stationary; stationary around trend and unit root models, each containing different types and number of breaks and different lag lengths. The procedures are used to test for structural breaks on 14 annual macroeconomic series and 11 natural resource price series. The results indicate that there are structural breaks in all of the natural resource series and most of the macroeconomic series. Many of the series had multiple breaks. Our findings regarding the existence of unit roots, having allowed for structural breaks in the data, are largely consistent with previous work.

Testing for non-stationarity and cointegration allowing for the possibility of a structural break: an application to EuroSterling interest rates

In this paper we examine the order of integration of EuroSterling interest rates by employing techniques that can allow for a structural break under the null and/or alternative hypothesis of the unit-root tests. In light of these results, we investigate the cointegrating relationship implied by the single, linear expectations hypothesis of the term structure of interest rates employing two techniques, one of which allows for the possibility of a break in the mean of the cointegrating relationship. The aim of the paper is to investigate whether or not the interest rate series can be viewed as I(1) processes and furthermore, to consider whether there has been a structural break in the series. We also determine whether, if we allow for a break in the cointegration analysis, the results are consistent with those obtained when a break is not allowed for. The main results reported in this paper support the conjecture that the ‘short’ Euro-currency rates are characterised as I(1) series that exhibit a structural break on or near Black Wednesday, 16 September 1992, whereas the ‘long’ rates are I(1) series that do not support the presence of a structural break. The evidence from the cointegration analysis suggests that tests of the expectations hypothesis based on data sets that include the ERM crisis period, or a period that includes a structural break, might be problematic if the structural break is not explicitly taken into account in the testing framework.

Reviewing the sustainability/stationarity of current account imbalances with tests for bounded integration

We investigate for 26 OECD economies whether their current account imbalances to GDP are driven by stochastic trends. Regarding bounded stationarity as the more natural counterpart of sustainability, results from Phillips–Perron tests for unit root and bounded unit root processes are contrasted. While the former hint at stationarity of current account imbalances for 12 economies, the latter indicate bounded stationarity for only six economies. Through panel-based test statistics, current account imbalances are diagnosed as bounded non-stationary. Thus, (spurious) rejections of the unit root hypothesis might be due to the existence of bounds reflecting hidden policy controls or financial crises.

MODELLING AND FORECASTING INFLATION RATES IN GHANA: AN APPLICATION OF SARIMA MODELS

Ghana faces a macroeconomic problem of inflation for a long period of time. The problem in somehow slows the economic growth in this country. As we all know, inflation is one of the major economic challenges facing most countries in the world especially those in African including Ghana. Therefore, forecasting inflation rates in Ghana becomes very important for its government to design economic strategies or effective monetary policies to combat any unexpected high inflation in this country. This paper studies seasonal autoregressive integrated moving average model to forecast inflation rates in Ghana. Using monthly inflation data from July 1991 to December 2009, we find that ARIMA (1,1,1)(0,0,1)12 can represent the data behavior of inflation rate in Ghana well. Based on the selected model, we forecast seven (7) months inflation rates of Ghana outside the sample period (i.e. from January 2010 to July 2010). The observed inflation rate from January to April which was published by Ghana Statistical Service Department fall within the 95% confidence interval obtained from the designed model. The forecasted results show a decreasing pattern and a turning point of Ghana inflation in the month of July.

Government spending and unemployment : An empirical study on Sweden, 1994-2012

The aim of the study was to see if any relationship between government spending andunemployment could be empirically found. To test if government spending affectsunemployment, a statistical model was applied on data from Sweden. The data was quarterlydata from the year 1994 until 2012, unit-root test were conducted and the variables wheretransformed to its first-difference so ensure stationarity. This transformation changed thevariables to growth rates. This meant that the interpretation deviated a little from the originalgoal. Other studies reviewed indicate that when government spending increases and/or taxesdecreases output increases. Studies show that unemployment decreases when governmentspending/GDP ratio increases. Some studies also indicated that with an already largegovernment sector increasing the spending it could have negative effect on output. The modelwas a VAR-model with unemployment, output, interest rate, taxes and government spending.Also included in the model were a linear and three quarterly dummies. The model used 7lags. The result was not statistically significant for most lags but indicated that as governmentspending growth rate increases holding everything else constant unemployment growth rateincreases. The result for taxes was even less statistically significant and indicates norelationship with unemployment. Post-estimation test indicates that there were problems withnon-normality in the model. So the results should be interpreted with some scepticism.

Testing common nonlinear features in vector nonlinear autoregressive models

This paper studies a special class of vector smooth-transition autoregressive (VSTAR) models that contains common nonlinear features (CNFs), for which we proposed a triangular representation and developed a procedure of testing CNFs in a VSTAR model. We first test a unit root against a stable STAR process for each individual time series and then examine whether CNFs exist in the system by Lagrange Multiplier (LM) test if unit root is rejected in the first step. The LM test has standard Chi-squared asymptotic distribution. The critical values of our unit root tests and small-sample properties of the F form of our LM test are studied by Monte Carlo simulations. We illustrate how to test and model CNFs using the monthly growth of consumption and income data of United States (1985:1 to 2011:11).

CO2 Emissions, GDP and trade : a panel cointegration approach

This paper examines the relationships among per capita CO2 emissions, per capita GDP and international trade based on panel data sets spanning the period 1960-2008: one for 150 countries and the others for sub-samples comprising OECD and Non-OECD economies. We apply panel unit root and cointegration tests, and estimate a panel error correction model. The results from the error correction model suggest that there are long-term relationships between the variables for the whole sample and for Non-OECD countries. Finally, Granger causality tests show that there is bi-directional short-term causality between per capita GDP and international trade for the whole sample and between per capita GDP and CO2 emissions for OECD countries