Trade shocks from BRIC to South Africa: A global VAR analysis

This paper studies the trade linkages between South Africa and the BRIC (Brazil, Russia, India and China) countries. We apply a global vector autoregressive model (global VAR) to investigate the degree of trade linkages and shock transmission between South Africa and the BRIC countries over the period 1995Q1–2009Q4. The model contains 32 countries and has two different estimations: the first one consists of 24 countries and one region, with the 8 countries in the euro area treated as a single economy; and the second estimation contains 20 countries and two regions, with the BRIC and the euro area countries respectively treated as a single economy. The results suggest that trade linkages exist between our focus economies; however the magnitude differs between countries. Shocks from each BRIC country are shown to have considerable impact on South African real imports and output.     

Forecasting the US real house price index: Structural and non-structural models with and without fundamentals

We employ a 10-variable dynamic structural general equilibrium model to forecast the US real house price index as well as its downturn in 2006:Q2. We also examine various Bayesian and classical time-series models in our forecasting exercise to compare to the dynamic stochastic general equilibrium model, estimated using Bayesian methods. In addition to standard vector-autoregressive and Bayesian vector autoregressive models, we also include the information content of either 10 or 120 quarterly series in some models to capture the influence of fundamentals. We consider two approaches for including information from large data sets — extracting common factors (principle components) in factor-augmented vector autoregressive or Bayesian factor-augmented vector autoregressive models as well as Bayesian shrinkage in a large-scale Bayesian vector autoregressive model. We compare the out-of-sample forecast performance of the alternative models, using the average root mean squared error for the forecasts. We find that the small-scale Bayesian-shrinkage model (10 variables) outperforms the other models, including the large-scale Bayesian-shrinkage model (120 variables). In addition, when we use simple average forecast combinations, the combination forecast using the 10 best atheoretical models produces the minimum RMSEs compared to each of the individual models, followed closely by the combination forecast using the 10 atheoretical models and the DSGE model. Finally, we use each model to forecast the downturn point in 2006:Q2, using the estimated model through 2005:Q2. Only the dynamic stochastic general equilibrium model actually forecasts a downturn with any accuracy, suggesting that forward-looking microfounded dynamic stochastic general equilibrium models of the housing market may prove crucial in forecasting turning points.     

The presence of unemployment hysteresis in the OECD: what can we learn from out-of-sample forecasts?

This paper investigates the relevance of unemployment hysteresis in seventeen OECD countries. We employ an out-of-sample forecast exercise in which a mean-reverting autoregressive model is compared to an autoregressive model with an imposed unit root. A substantial difference in forecasting performance between the two models is established for many countries, but the results are mixed in their strength. The evidence for unemployment hysteresis in Austria, Finland, Iceland, Israel, Italy, Japan and Sweden is, however, convincing. For no country can unambiguous support for a mean reverting unemployment rate be found.     

Regime-switching purchasing power parity in Latin America: Monte Carlo unit root tests with dynamic conditional score

We suggest a Monte Carlo simulation-based unit root test of the purchasing power parity theory for Latin American countries. Under the null hypothesis, we use a Markov regime-switching (MS) model with unit root in the conditional location and MS volatility dynamics. Under the alternative hypothesis, the proposed test incorporates Markov regime-switching autoregressive moving average (MS-ARMA) plus MS volatility dynamics. Under both the null and alternative hypotheses, one of the volatility models estimated is Beta-t-EGARCH, which is a recent dynamic conditional score volatility model. We use data on real effective exchange rate time series for 14 Latin American countries. For each country, we estimate by Monte Carlo simulation the critical values of the unit root test. We provide an economic discussion of the unit root test results and also study the robustness of MS-ARMA plus MS volatility with respect to smooth transition autoregressive models with Fourier function.     

Do we need a global VAR model to forecast inflation and output in South Africa?

This study determines whether the global vector autoregressive (GVAR) approach provides better forecasts of key South African variables than a vector error correction model (VECM) and a Bayesian vector autoregressive (BVAR) model augmented with foreign variables. The article considers both a small GVAR model and a large GVAR model in determining the most appropriate model for forecasting South African variables. We compare the recursive out-of-sample forecasts for South African GDP and inflation from six types of models: a general 33 country (large) GVAR, a customized small GVAR for South Africa, a VECM for South Africa with weakly exogenous foreign variables, a BVAR model, autoregressive (AR) models and random walk models. The results show that the forecast performance of the large GVAR is generally superior to the performance of the customized small GVAR for South Africa. The forecasts of both the GVAR models tend to be better than the forecasts of the augmented VECM, especially at longer forecast horizons. Importantly, however, on average, the BVAR model performs the best when it comes to forecasting output, while the AR(1) model outperforms all the other models in predicting inflation. We also conduct ex ante forecasts from the BVAR and AR(1) models over 2010:Q1–2013:Q4 to highlight their ability to track turning points in output and inflation, respectively.     

Forecast accuracy of small and large scale dynamic factor models in developing economies

Developing economies usually present limitations in the availability of economic data. This constraint may affect the capacity of dynamic factor models to summarize large amounts of information into latent factors that reflect macroeconomic performance. This paper addresses this issue by comparing the accuracy of two kinds of dynamic factor models at GDP forecasting for six Latin American countries. Each model is based on a dataset of different dimensions: a large dataset composed of series belonging to several macroeconomic categories (large scale dynamic factor model) and a small dataset with a few prescreened variables considered as the most representative ones (small scale dynamic factor model). Short‐term pseudo real time out‐of‐sample forecast of GDP growth is carried out with both models reproducing the real time situation of data accessibility derived from the publication lags of the series in each country. Results (i) confirm the important role of the inclusion of latest released data in the forecast accuracy of both models, (ii) show better precision of predictions based on factors with respect to autoregressive models and (iii) identify the most adequate model for each country according to availability of the observed data.     

The global effects of productivity gains in Asian emerging economies

This paper investigates international responses of key macroeconomic variables to simultaneous shocks to productivity in the traded sector in eight Asian emerging and developing countries. We use panel estimation techniques to construct component sub-models in a thirty country global vector autoregressive (GVAR) model. We identify the shocks by using sign restricted impulse responses. We find that increases in traded-sector productivity in Asian emerging and developing countries have a positive effect on economic growth and international trade for most countries.     

Macroeconomic variables and the sovereign risk premia in EMU,non-EMU EU,and developed countries

This project studies and models key macroeconomic variables and their impact on sovereign risk premia across select European economies and developed countries. The sample is divided into three groups of countries: those in the European Monetary Union (EMU); the standalone economies outside the EMU but members of the broader European Union (EU); and other developed economies. The main subject of examination across all three groups is the impact of macroeconomic variables on sovereign borrowing costs. EU countries have experienced high financial stress and a rapid rise in the credit default swaps (CDS) spreads during the EMU debt crisis. A nonlinear vector smooth transition autoregressive model is applied to investigate such a regime change in the finance-output link using sovereign CDS and industrial production index. The paper finds that regime-switching takes place rather suddenly in most EMU countries. The study concludes that due to the potential spillover effects in the EU as a whole, the individual country macroeconomic indicators were less reflected in the financial stress and spillover and contagion effects became dominant.     

Sovereign default risk and state-owned bank fragility in emerging markets: evidence from China and Russia

In this paper we investigate the interdependence of the sovereign default risk and banking system fragility in two major emerging markets, China and Russia, using credit default swaps as a proxy for default risk. Both countries’ banking industries have strong ties with their governments and public sector, even after a series of significant reforms in the last two decades. Our analysis is built on the case studies of each country’s two biggest banks. We employ a bivariate vector autoregressive (VAR) and vector error correction (VECM) framework to analyse the short- and long-run dynamics of the chosen CDS prices. We use Granger causality to describe the direction of the discovered dynamics. We find evidence of a stable long-run relationship between sovereign and bank CDS spreads in the chosen time period. The more stable relationship is found in cases where the biggest state-owned universal banks in emerging markets are closely managed by the government. But the fragility of those banks does not directly affect the state of public finances. However, in cases where state-owned banks directly participate in large governmental projects, banking fragility may result in the deterioration of state funds, while raising the risk of sovereign default.     

Linking global economic dynamics to a South African-specific credit risk correlation model

In order to address practical questions in credit portfolio management it is necessary to link the cyclical or systematic components of firm credit risk with the firm's own idiosyncratic credit risk as well as the systematic credit risk component of every other exposure in the portfolio. This paper builds on the methodology proposed by Pesaran, Schuermann, and Weiner [Pesaran, M.H., Schuermann, T., and Weiner, S.M., (2004), Modeling regional interdependencies using a global error correcting macroeconometric model, Journal of Business and Economic Statistics, 22, 2, 129–169.] and supplemented by Pesaran, Schuermann, Treutler and Weiner [Pesaran, M.H., Schuermann, T., Treutler, B., and Weiner, S.M., (2006), Macroeconomic dynamics and credit risk: a global perspective, Journal of Money, Credit, and Banking, Volume 38, Number 5, August 2006, 1211–1261.] which has made a significant advance in credit risk modelling in that it avoids the use of proprietary balance sheet and distance-to-default data, focusing on credit ratings which are more freely available.In this paper a country-specific macroeconometric risk-driver engine which is compatible with and could feed into the GVAR model and framework of PSW (2004) is constructed, using vector error-correcting (VECM) techniques. This allows conditional loss estimation of a South African-specific credit portfolio but also opens the door for credit portfolio modelling on a global scale, as such a model can easily be linked to the GVAR model. The set of domestic factors is extended beyond those used in PSW (2004) in such a way that the risk-driver model is applicable for both retail and corporate credit risk. As such, the model can be applied to a total bank balance sheet, incorporating the correlation and diversification between both retail and corporate credit exposures.Assuming statistical over-identification restrictions, the results indicate that it is possible to construct a South African component for the GVAR model that can easily be integrated into the global component. From a practical application perspective the framework and model is particularly appealing since it can be used as a theoretically consistent correlation model within a South African-specific credit portfolio management tool.     

Exports and economic growth in industrialized countries

The prima-facie causal relationships between growth, exports and factor inputs (capital and labour) are investigated in five industrialized countries (germany, Itlay, Japan, United Kingdom and United States) over the period 1960–87 by analysing a four-variable vector autoregressive (VAR) model for each country. Our results indicate that Germany and Japan experienced export-led growth. Reverse causality between exports and growth is found in the case of the US and UK, while to causal relationship between exports and output is found for Itlay.     

Forecasting the barbados money supply

The purpose of this paper is to provide an adequate forecasting method for the money supply in the Barbadian economy. This would assist the Central Bank in making decisions on monetary intervention. The performance of ARIMA and vector autoregressive forecasting models are investigated along with combinations of these models. The results of this study suggest that there are reasonable options available for obtaining reliable forecasts of the Barbados money supply. Our findings indicate that seasonal factors and interest rate effects should be comprehended within the forecasting model. We accomplished this through a combination forecasting procedure in which seasonal effects are captured by an ARIMA model and interest rates are introduced through a vector autoregressive forecasting model as exogenous variables.     

Bilateral and regional trade elasticities of the EU

The traditional way of assessing the impact of currency depreciation and income on the trade balance has been to estimate the elasticity of trade volume to relative prices and income. The previous studies examine the problems associated with using aggregate data. The recent studies rely on bilateral data, yet another problem is that data for export and import prices are not available. Thus, this study proposes an alternative way of assessing the impact of currency depreciation by using the real exchange rate and the impact of income on bilateral trade. The models are applied between the EU and its major trading partners. Furthermore, the analysis includes the six major trading regions along side the eight major trading countries for 1980–2007, on the quarterly basis. This article uses the autoregressive distributive lag (ARDL) approach advocated by Pesaran and Pesaran (1997). Our results indicate a higher importance of income compared to the real exchange rate in defined bilateral export and import demand functions. In addition, the applied CUSUM and CUSUMSQ stability tests confirm the stability of estimated coefficients in most cases.     

Financial integration and the construction of historical financial data for the Euro Area

Time series analysis for the Euro Area requires the availability of sufficiently long historical data series, but the appropriate construction methodology has received little attention. The benchmark dataset, developed by the European Central Bank for use in its Area Wide Model (AWM), is based on fixed-weight aggregation across countries with historically distinct monetary policies and financial markets of varying international importance. This paper proposes a new methodology for producing back-dated financial series for the Euro Area, that is based on the time-varying distance of periphery countries from core countries with respect to monetary integration. Historical decompositions of the residuals of vector autoregressive models of the Euro Area economy are then used to explore and compare the monetary policy implications of using the new methodology versus the use of AWM fixed weight series.     

Evaluating a Global Vector Autoregression for Forecasting

Global vector autoregressions (GVARs) have several attractive features: multiple potential channels for the international transmission of macroeconomic and financial shocks, a standardized economically appealing choice of variables for each country or region examined, systematic treatment of long-run properties through cointegration analysis, and flexible dynamic specification through vector error correction modeling. Pesaran et al. (2009) generate and evaluate forecasts from a paradigm GVAR with 26 countries, based on Dées, di Mauro et al. (2007). The current paper empirically assesses the GVAR in Dées, di Mauro et al. (2007) with impulse indicator saturation (IIS)??a new generic procedure for evaluating parameter constancy, which is a central element in model-based forecasting. The empirical results indicate substantial room for an improved, more robust specification of that GVAR. Some tests are suggestive of how to achieve such improvements.     

Is external debt sustainable? A probabilistic approach

We develop a probabilistic approach to measure a country's external debt sustainability. Using data on international investment position and balance of payments from the International Monetary Fund, we estimate a vector autoregressive model for 38 countries (11 developed and 27 developing). Using the estimated parameters, we perform a Monte Carlo simulation to compute the distribution of the capacity to repay for each country. A large portion of the projected distribution to the right of current debt is a warning indicator, signalling the need for devaluation. We provide simulations for each country. One scenario is where the discount factor is lower than 1. According to the literature, this situation should prevail in the medium and long run. A quite different situation is where external sustainability is achieved because of a simulated discount factor of more than 1. Here, interest on debt is lower than GDP growth. This situation is associated with dynamic inefficiency. The results suggest that flight to safety is penalising some developing countries, whilst benefiting some developed countries.     

Seasonal cointegration analysis of German consumption function

The main purpose of this paper is to investigate the West-German consumption process depending on wealth and income with seasonal cointegration techniques using the framework of vector autoregressive models to capture the seasonal pattern of the series. The vector autoregressive models are the basis of a dynamic analysis by impulse response functions where the asymptotic distributions of the estimators are given. In the empirical part of the paper evidence is found for seasonal and nonseasonal cointegration relations among the variables. The response functions of consumption and income show a strong influence of wealth innovations. Moreover, income and consumption reactions present outstanding seasonal pattern.     

Threshold models for trended time series

This paper presents the theoretical development of a new threshold autoregressive model based on trended time series. The theoretical arguments underlying the model are outlined and a nonlinear economic model is used to derive the specification of the empirical econometric model. Estimation and testing issues are considered and analysed. Additionally we apply the model to the empirical investigation of U.S. GDP.This paper is the result of work carried out for the author's Ph.D. thesis. I would like to thank Hashem Pesaran for his help, encouragement and insights during the preparation of this paper. I also thank Gary Koop and Sean Holly for helpful comments. Financial assistance from the Economic and Social Research Council is gratefully acknowledged.     

A new approach in multivariate time series specification

Within the study of multivariate time series, this work is centered on vector autoregressive moving average (VARMA) models, specifically on the specification stage. Until now, numerous procedures have been proposed to resolve the problem of identifying the dynamic behavior in a VARMA model framework. A new strategy is added to specify VARMA models justified by results within the field of matrix Padé approximation. Besides contributing a characterization of these models, alternative methods are added to those already in the literature to deal with the problems of identifiability and exchangeability. The obtained characterizations have the advantage of graphically presenting the results in tables for direct interpretation. The proposed technique is illustrated by means of a theoretical example, a simulated model, and data from economic variables (already dealt with by other authors) in order to compare results.     

Evidence for Financial Contagion in Endogenous Volatile Periods

The objective of this study is to analyze cross‐border contagious dynamics in both foreign exchange markets and stock exchange markets. Propagation is analyzed with respect to the transmission of excessive volatility that is endogenously determined. The contagion process is discussed in the context of financial systems, foreign direct investments and trade. Implementing a vector autoregressive‐multivariate generalized autoregressive conditional heteroskedasticity (VAR‐MGARCH) model, we show that country‐specific turbulence in financial markets is able to create unanticipated financial contagion across countries. Diversified trade and financial relations decrease the risk of exposure to contagion from external markets. The world's largest economies, however, play a price‐setter role, and diversification is of secondary importance. Asymmetric transmission of the empirically predicted contagion prevails in the latter case.