Is per capita real GDP stationary in five southeastern European countries? Fourier unit root test

This study uses the newly developed Fourier unit root test advanced by Enders and Lee (2004, 2009) to investigate the time-series properties of real GDP (Gross Domestic Product) for five Southeastern European countries for the period from 1969 to 2009. The empirical results from several conventional unit root tests indicate that the per capita real GDP for all of the countries studied are non-stationary; however, when Enders and Lee (2004, 2009) Fourier unit root tests are conducted, one rejects the unit root hypothesis of real GDP per capita in all countries under study. These results have important policy implications for these five Southeastern European countries under study.     

Applying a microfounded-forecasting approach to predict Brazilian inflation

We investigate whether combining forecasts from surveys of expectations is a helpful empirical strategy for forecasting inflation in Brazil. We employ the FGV–IBRE Economic Tendency Survey, which consists of monthly qualitative information from approximately 2000 consumers since 2006, and also the Focus Survey of the Central Bank of Brazil, with daily forecasts since 1999 from roughly 250 professional forecasters. Natural candidates to win a forecast competition in the literature of surveys of expectations are the (consensus) cross-sectional average forecasts (AF). We first show that these forecasts are a bias-ridden version of the conditional expectation of inflation using the no-bias tests proposed in Issler and Lima (J Econom 152(2):153–164, 2009) and Gaglianone and Issler (Microfounded forecasting, 2015). The results reveal interesting data features: Consumers systematically overestimate inflation (by 2.01 p.p., on average), whereas market agents underestimate it (by 0.68 p.p. over the same sample). Next, we employ a pseudo out-of-sample analysis to evaluate different forecasting methods: the AR(1) model, the Granger and Ramanathan (J Forecast 3:197–204, 1984) forecast combination (GR) technique, a Phillips-curve based method, the Capistrán and Timmermann (J Bus Econ Stat 27:428–440, 2009) combination method, the consensus forecast (AF), the bias-corrected average forecast (BCAF), and the extended BCAF. Results reveal that: (i) the MSE of the AR(1) model is higher compared to the GR (and usually lower compared to the AF); and (ii) the extended BCAF is more accurate than the BCAF, which, in turn, dominates the AF. This validates the view that the bias corrections are a useful device for forecasting using surveys. The Phillips-curve based method has a median performance in terms of MSE, and the Capistrán and Timmermann (2009) combination method fares slightly worse.     

European commission’s fiscal forecasts in CEE countries: a thorough assessment

ABSTRACT

This paper assesses European Commission’s fiscal forecasts for a sample of 10 Central and Eastern European countries between 2005 and 2015. The analysis focus on forecasts of the budget balance, revenues, expenditures and debt and pays special attention to dynamics around business cycle turning points. Results suggest that the distribution of projection errors appears to be biased towards optimism of fiscal aggregates and accuracy increases as the forecast horizon shortens. We also find evidence of “forecast smoothing”. In addition, we find that, on average, the extent of optimism seems to increase during recessions (and to a lesser extent during recoveries). Moreover, errors in forecasting fiscal variables can be explained by forecasts errors of real GDP growth and inflation.     

The accuracy of OECD forecasts

This paper examines the accuracy and properties of forecasts by the OECD for 24 countries and 8 variables. First the forecasts made in December of yeart?1 for yeart are examined, with the largest errors being for investment, industrial production and foreign balance. Next the way forecasts are revised between December and July is considered. Systematic revisions occur for Iceland, Turkey and Luxembourg. Finally the accuracy of forecasts made before, during and after the 1979 oil price rises are compared, and no evidence of a worsening of accuracy is found.     

Predicting U.S. recessions through a combination of probability forecasts

Recently De Luca and Carfora (Statistica e Applicazioni 8:123–134, 2010) have proposed a novel model for binary time series, the Binomial Heterogenous Autoregressive (BHAR) model, successfully applied for the analysis of the quarterly binary time series of U.S. recessions. In this work we want to measure the efficacy of the out-of-sample forecasts of the BHAR model compared to the probit models by Kauppi and Saikkonen (Rev Econ Stat 90:777–791, 2008). Given the substantial indifference of the predictive accuracy between the BHAR and the probit models, a combination of forecasts using the method proposed by Bates and Granger (Oper Res Q 20:451–468, 1969) for probability forecasts is analyzed. We show how the forecasts obtained by the combination between the BHAR model and each of the probit models are superior compared to the forecasts obtained by each single model.     

A spatial econometric analysis of the regional growth and volatility in Europe

Based on a sample of 1,084 European regions (EU15) from 1995 to 2004, we estimate the relationship between the average growth rate of GDP per capita and the volatility of the growth rate allowing for spatial effects. The spatial lag and spatial error models show that the regional per capita growth rate and volatility are significantly positively related on average. However, the inclusion of country interaction terms reveals that the volatility impact is not uniform across countries. In particular, the relationship between growth and volatility is significantly positive for the majority of countries but significantly negative for three countries (namely Finland, Italy, and Ireland).

The relationship between insurance and economic growth in Europe: a theoretical and empirical analysis

The role of insurance companies, although growing in importance in financial intermediation, has received less attention than bank and stock markets and if so, mainly as a provider of risk transfer in single country or very heterogeneous samples. We investigate both the impact of insurance investment and premiums on GDP growth in Europe. We conduct a cross-country panel data analysis from 1992 to 2005 for 29 European countries. We find a positive impact of life insurance on GDP growth in the EU-15 countries, Switzerland, Norway and Iceland. For the New EU Member States from Central and Eastern Europe, we find a larger impact for liability insurance. Furthermore our findings emphasise the impact of the real interest rate and the level of economic development on the insurance-growth nexus. We argue that the insurance sector needs to be paid more attention in financial sector analysis and macroeconomic policy.

Regulation and revenue

The power to tax and the power to regulate are often analyzed separately. We argue that, when in the hands of a single authority, the power to tax may act as a check on the power to regulate, thereby discouraging regulations that adversely affect GDP, and promoting regulations that enhance GDP. This effect will be stronger the higher are (marginal) taxes. This argument is used both to suggest an explanation for the observed positive correlation between high taxes and economic freedom, and to warn against the granting of regulatory but not fiscal powers at the European level.

Uncertainty avoidance and the rate of business ownership across 21 OECD countries, 1976–2004

Persistent differences in the level of business ownership across countries have attracted the attention of scientific as well as political debate. Cultural as well as economic influences are assumed to play a role. This paper deals with the influence of cultural attitudes towards uncertainty on the rate of business ownership across 21 OECD countries. First, the concepts of uncertainty and risk are elaborated, as well as their relevance for entrepreneurship. An occupational choice model is introduced to underpin our reasoning at the macro-level. Second, regression analysis using pooled macro data for 1976, 1990 and 2004 and controlling for several economic variables, yields evidence that uncertainty avoidance is positively correlated with the prevalence of business ownership. According to our model, a restrictive climate of large organizations in high uncertainty avoidance countries pushes individuals striving for autonomy towards self-employment. Regressions for these 3 years separately show that in 2004, this positive correlation is no longer found, indicating that a compensating pull of entrepreneurship in countries with low uncertainty avoidance may have gained momentum in recent years. Third, an interaction term between uncertainty avoidance and GDP per capita in the pooled panel regressions shows that the historical negative relationship between GDP per capita and the level of business ownership is substantially weaker for countries with lower uncertainty avoidance. This suggests that rising opportunity costs of self-employment play a less important role in this cultural environment, or are being compensated by increasing entrepreneurial opportunities.

Forecast combination for discrete choice models: predicting FOMC monetary policy decisions

This paper provides a methodology for combining forecasts based on several discrete choice models. This is achieved primarily by combining one-step-ahead probability forecasts associated with each model. The paper applies well-established scoring rules for qualitative response models in the context of forecast combination. Log scores, quadratic scores and Epstein scores are used to evaluate the forecasting accuracy of each model and to combine the probability forecasts. In addition to producing point forecasts, the effect of sampling variation is also assessed. This methodology is applied to forecast US Federal Open Market Committee (FOMC) decisions regarding changes in the federal funds target rate. Several of the economic fundamentals influencing the FOMC’s decisions are integrated, or I(1), and are modeled in a similar fashion to Hu and Phillips (J Appl Econom 19(7):851– 867, 2004). The empirical results show that combining forecasted probabilities using scores generally outperforms both equal weight combination and forecasts based on multivariate models.     

Exchange market pressure: some caveats in empirical applications

The Exchange Market Pressure (EMP) index, developed by Eichengreen et al. (1994 Eichengreen, B, Rose, AK and Wyplosz, C. 1994. Speculative attacks on pegged exchange rates: an empirical exploration with special reference to the European monetary system, NBER Working Paper No. 4898  [Google Scholar]), is widely used as a tool to signal whether pressure on a currency is softened or warded off through monetary authorities’ interventions or, rather, a currency crisis has originated. In this article we show how the index is sensitive to some assumptions behind the aggregation of the information available (exchange rates, interest rates and reserves), especially when emerging countries are involved. Specifically, we address the way exchange rate variations are computed and the impact of different definitions of the reserves, and we question the constancy of the weights adopted. These issues compound with the choice of a fixed threshold when crisis episodes are identified through the EMP index. As a result, one should exert caution in subsequent econometric analyses where a dependent binary variable is built to identify crisis periods.     

The macroeconomic costs of conflict

Macroeconomic costs of conflict are generally very large, with GDP per capita about 28 percent lower ten years after conflict onset. This is overwhelmingly driven by private consumption, which falls by almost 25 percent ten years after conflict onset. Conflict is also associated with dramatic declines in official trade, with exports (imports) estimated to be 58 (34) percent lower ten years after conflict onset. The onset of conflict often also induces significant refugee outflows to neighboring non-advanced countries in the short run, and relatively small but very persistent refugee outflows to advanced countries over the long run. To alleviate reverse causality concerns between GDP and conflict onset, we control for pre-conflict GDP forecasts from the IMF World Economic Outlook and show that similar results are obtained with and without pre-conflict GDP forecasts.     

Germany and Italy: conflicting policy paradigms towards European monetary integration?

In the literature on European monetary integration Germany and Italy are mostly strongly contrasted. However, this paper argues that there were important similarities between the policy paradigms in these two countries, in particular if a broader historical perspective is adopted. This work analyses the policy paradigms towards European monetary integration in Italy and Germany. Moreover, it contextualises these paradigms into the national institutional setting: while Germany was characterised by power sharing institutions, Italy featured power fragmentation (something which also affected the economic performance of both countries). There were significant differences between the policy paradigms of foreign policy-makers and economic policy-makers. Foreign policy makers, in both countries, under the influence of a European federalist vision, were strongly in favour of European monetary integration. These beliefs of foreign policy decision makers were crucial in charting EMU policy at history-making moments. The pro EMU policy paradigms of foreign policymakers contrasted, during most of the period covered, with the more sceptical beliefs of economic policy makers. In both countries, economic policy-makers, at different moments, had doubts whether enough “convergence” had been reached to make a more stable exchange rate system sustainable.

How productivity and domestic output are related to exports and foreign output in the case of Sweden

In this paper we examine the relationships between two sets of three variables: Swedish real exports, Swedish real GDP, and foreign real GDP in one set; and Swedish real exports, Swedish total factor productivity, and foreign real GDP in the other set. The foreign real GDP facing Sweden is proxied by total OECD real GDP minus Sweden's real GDP. Multivariate tests for integration and cointegration show that the variables in each model are cointegrated. We also perform Granger causality tests on these variables in our examination using the Toda-Yamamoto procedure. We discover bi-directional causality between Swedish real exports and Swedish real GDP (or Swedish total factor productivity). Foreign real GDP is shown to Granger cause Swedish real exports, but no significant causation of foreign real GDP on either domestic GDP or total factor productivity was found. A change in foreign real GDP thus appears to affect Swedish output and productivity only indirectly, through changes in Swedish exports. JEL classification:F41, F43, C30, C32     

Methodological Procedure for Estimating Brazilian Quarterly GDP Series

This paper presents a methodology for estimating the Brazilian GDP quarterly series in the period between 1960–1996. Firstly, an Engle–Granger’s static equation is estimated using GDP yearly data and GDP-related variables. The estimated coefficients from this regression are then used to obtain a first estimation of the quarterly GDP, with unavoidable measurement errors. The subsequent step is entirely based on benchmarking models estimated within a state space framework and consists in improving the preliminary GDP estimation in order to both eliminate as much as possible the measurement error and that the sum of the quarterly values matches the annual GDP.

Does a non-linear mean reverting process characterize real GDP movements?

This paper uses non-linear models to investigate non-stationarity of real GDP per capita for seven OECD countries over the period 1900–2000. Unit root tests based on non-linear models are more powerful than traditional ADF statistics in rejecting the null unit root hypothesis. Empirical results show that, contrary to what the linear ADF statistics suggest, stationarity characterizes five out of the seven countries. This finding stands at variance with other recent studies which conclude that movements in real GDP per capita can be characterized as a non-stationary process.

Testing poolability in a system of dynamic regressions with nonspherical disturbances

This study analyzes the testing of cross-equation restrictions within a set of regression equations. Through Monte Carlo experiments we examine the actual size of various asymptotic procedures for testing the poolability hypothesis, i.e., equal slope vectors across individual equations. Regression models with both lagged dependent variable regressors and nonspherical disturbances are considered. In these models we find that the performance in finite samples of classical asymptotic test procedures using critical values from either or ² approximations is often rather poor. However, employing the original test statistics with bootstrapped critical values leads to much more accurate inference in finite samples. In an empirical analysis of panel data on GDP growth and unemployment rates in OECD countries it is shown that classical asymptotic tests and bootstrap procedures may lead to conflicting test outcomes. I am indebted to Peter Boswijk, Jan Kiviet, Peter Vlaar, the associate editor and 2 anonymous referees for their constructive comments. I want to thank Geoffrey Garrett for kindly making available his data.     

Interest rate assumptions and predictive accuracy of central bank forecasts

The interest rate assumptions for macroeconomic forecasts differ among central banks. Common approaches are given by the assumptions that interest rates remain constant over the forecast horizon, follow a path as expected by market participants or follow a path as expected by the central bank itself. Theoretical papers such as Svensson (The instrument-rate projection under inflation targeting: the Norwegian example. Centre for European Policy Studies Working Paper (127), 2006) and Galí (J Monet Econ 58:537–550, 2011) suggest an accuracy ranking for these forecasts, from employing central bank expectations yielding the highest forecast accuracy to conditioning on constant interest rates yielding the lowest. Yet, when investigating the predictive accuracy of the Bank of England’s and the Banco Central do Brasil’s forecasts for interest rates, inflation and output growth, we hardly find any significant differences between forecasts based on the different interest rate paths. Our results suggest that the choice of the interest rate assumption appears to be of minor relevance empirically.     

Is PMI Useful in Quarterly GDP Growth Forecasts for India? An Exploratory Note

This paper examines the relationship between India’s quarterly overall GDP, manufacturing GDP and services GDP and the corresponding monthly data on overall manufacturing and services PMI for the period January 2006 to July 2014. The objective is to see if the two overall PMIs are related to the level and quarterly growth rate of overall GDP and its chosen components. Considering the quarterly time series nature of the data set, the HEGY equation of Hylleberg et al. (J Econom 44:215–238, 1990) extended by adding the PMI variables as exogenous regressors is used as the regression mode to relate a GDP level/growth rate variable to the two overall PMI variables. The results show that the three GDP level variables, but none of the GDP growth rate variables, have significant positive correlation with services PMI, but not with manufacturing PMI. Finally, the marginal effect of services PMI on manufacturing GDP level is found to be the largest, followed by that for overall GDP level and services GDP level.

     

Does Benford’s Law hold in economic research and forecasting?

First and higher order digits in data sets of natural and socio-economic processes often follow a distribution called Benford’s law. This phenomenon has been used in business and scientific applications, especially in fraud detection for financial data. In this paper, we analyse whether Benford’s law holds in economic research and forecasting. First, we examine the distribution of regression coefficients and standard errors in research papers, published in Empirica and Applied Economics Letters. Second, we analyse forecasts of GDP growth and CPI inflation in Germany, published in Consensus Forecasts. There are two main findings: The relative frequencies of the first and second digits in economic research are broadly consistent with Benford’s law. In sharp contrast, the second digits of Consensus Forecasts exhibit a massive excess of zeros and fives, raising doubts on their information content.