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.     

Is there a “real divergence” in the European Union? A comment

In a recently published paper, Hein and Truger [Hein, E., Truger, A., 2005. European monetary union: nominal convergence, real divergence and slow growth? Structural Change and Economic Dynamics 16, 7–33], state that real per capita income in the European Union has developed a long-run process of divergence (real divergence). We discuss their approach towards measuring cross-national income inequality and its evolution over time, and argue that there are good reasons to pursue alternative procedures. We show that alternative measures yield different conclusions concerning the convergence/divergence of prosperity across the EU. Especially, as the divergence result is driven by one or two countries with almost negligible population shares, accounting for population size implies that cross-national income dispersion in the EU has decreased at least since the mid-1990s.     

How flexible are real wages in EU countries? A panel investigation

We estimate the degree of real wage flexibility in 19 EU countries in a wage Phillips curve panel framework. We find evidence for a reaction of wage growth to unemployment and productivity growth. The degree of real wage flexibility tends to be larger in the central and eastern European (CEE) countries than in the euro area; weaker in downturns than during upswings. There exists an inflation threshold, below which real wage flexibility is low. We also find that a part of the heterogeneity in real wage flexibility and unemployment may be related to differences in the wage bargaining institutions.     

Sentiment dynamics and stock returns: the case of the German stock market

We use weekly survey data on short-term and medium-term sentiment of German investors in order to study the causal relationship between investors’ mood and subsequent stock price changes. In contrast to extant literature for other countries, a trivariate vector autoregression for short-run sentiment, medium-run sentiment, and stock index returns allows to reject exogeneity of returns. Depending on the chosen VAR specification, returns are found to either follow a feedback process caused by medium-run sentiment, or returns form a simultaneous systems together with the two sentiment measures. An out-of-sample forecasting experiment on the base of estimated subset VAR models shows significant exploitable linear structure. However, trading experiments do not yield convincing evidence of significant economic gains from the VAR forecasts, and it appears that predictability of returns from sentiment decreases during the recent market gyrations.     

Option-implied preferences adjustments, density forecasts, and the equity risk premium

The main objective of this paper is to analyse the value of information contained in prices of options on the IBEX 35 index at the Spanish Stock Exchange Market. The forward looking information is extracted using implied risk-neutral density functions estimated by a mixture of two-lognormals and several alternative risk adjustments. Our results show that, between October 1996 and March 2000, we can reject the hypothesis that the risk-neutral densities provide accurate predictions of the distributions of future realisations of the IBEX 35 index at 4- and 8-week horizons. When forecasting through risk-adjusted densities the performance of this period is statistically improved and we no longer reject that hypothesis. We show that risk adjustments based on a power specification for the stochastic discount factor—which is the approach used so far in the literature that derives the objective density function from option prices- generates an excessive volatility of risk premia. We use alternative risk adjustments and find that the forecasting performance of the distribution improves slightly in some cases when risk aversion is allowed to be time-varying. Finally, from October 1996 to December 2004, the ex-ante risk premium perceived by investors and that are embedded in option prices is between 12 and 18% higher than the premium required to compensate the same investors for the realised volatility in stock market returns.      

Forecasting US recessions with macro factors

Dynamic factors estimated from panels of macroeconomic indicators are used to predict future recessions using probit models. Three factors are considered: a bond and exchange rates factor, a stock market factor and a real activity factor. Three results emerge. First, models that use only financial indicators exhibit a large deterioration in fit after 2005. Second, models that use factors yield better fit than models that use indicators directly. Out-of-sample forecasting exercises confirm these results for 3-, 6- and 12-month horizons using both ex-post revised data and real-time data. Third, results show evidence that data revisions affect factors less than individual indicators.     

Market‐Based Measures of Monetary Policy Expectations and Their Evolution Since the Introduction of the Euro

The paper considers the relation between monetary policy expectations and financial markets in the case of Europe. A number of money market instruments are compared, with the result that the 1‐month forward interest rates extracted from the Libor yield curve has the best prediction power of the future monetary policy path. These forward rates have been used to study the evolution of market expectations regarding the monetary policy of the European Central Bank (ECB). The sharp increases and the following decreases in interest rates during 2000–2001 have reduced the predictive power of money market instruments, but smoother management of interest rates and better communication from the ECB has helped to improve the forecasting power of money market instruments.     

The trade impact of European Union agricultural preferences

We assess the impact on agricultural trade of European Union (EU) trade policies, using a gravity model based on disaggregated trade flows from 161 developing countries (DCs) to 15 EU member countries. We use a sample selection framework to account for potential selection bias of positive trade flows and provide an explicit measure for relative preference margins. From a policy perspective, our results debunk some of the most widespread criticisms of preferential policies: EU preferences matter and have a positive impact on DCs agricultural exports at both the extensive and intensive margins, although with significant differences across sectors.     

Forecasting the yield curve and the role of macroeconomic information in Turkey

In this study we investigate the yield curve forecasting performance of Dynamic Nelson–Siegel Model (DNS), affine term structure VAR model (ATSM VAR) and principal component model (PC) in Turkey. We also investigate the role of macroeconomic variables in forecasting the yield curve. We have reached numbers of important results: 1—Macroeconomic variables are very useful in forecasting the yield curve. 2—The forecasting performances of the models depend on the period under review. 3—Considering the structural break which associates with change in monetary policy leads models to produce better forecasts than the random walk. 4—The role of exchange rate should not be ruled out in forecasting the yield curve in an emerging market like Turkey.     

So alike,yet so different: Comparing fiscal multipliers across EU members and candidates

We estimate, using a Panel Vector Autoregressive approach and data from 2001Q1 to 2017Q1, the fiscal multipliers of the European Union (EU) members and candidates. These countries are grouped according to their stages of integration: original members, new Eurozone members, and candidates for the Eurozone and the EU itself. For each group, we assess the impact of a positive spending shock (expansionary) or a positive tax shock (contractionary) on GDP. Our findings suggest that: (i) rising government spending increases GDP in both the EU and Eurozone candidates (Keynesian multipliers), but slightly decreases it in the Eurozone members (non-Keynesian multipliers); (ii) higher taxes are associated with mixed results in terms of GDP dynamics - both increases and decreases in terms of GDP are found - in the four country groups (suggesting the presence of Keynesian and non-Keynesian multipliers). Overall, these outcomes indicate that spending multipliers are, compared to tax multipliers, more sensitive to European Union or Eurozone membership.     

Forecasting industrial production in the Euro area

The creation of the Euro area has increased the importance of obtaining timely information about short-term changes in the area's real activity. In this paper we propose a number of alternative short term forecasting models, ranging from simple ARIMA models to more complex cointegrated VAR and conditional models, to forecast the index of industrial production in the euro area. A conditional error-correction model in which the aggregate index of industrial production for the area is explained by the US industrial production index and the business confidence index from the European Commission harmonised survey on manufacturing firms achieves the best score in terms of forecasting capacity. First version received: Jan. 2000/Final version received: March 2000     

OWA-based ANFIS model for TAIEX forecasting

In stock market forecasting, high-order time-series models that use previous several periods of stock prices as forecast factors are more reasonable to provide a superior investment portfolio for investors than one-order time-series models using one previous period of stock prices. However, in forecasting processes, it is difficult to deal with high-order stock data, because it is hard to give a proper weight to each period of past stock price, reduce data dimensions without losing stock information, and produce a comprehensive forecasting result based on stock data with nonlinear relationships.Additionally, there are two more drawbacks to past time-series models: (1) some assumptions (Bollerslev, 1986; Engle, 1982) about stock variables are required for statistical methods, such as the autoregressive model (AR) and autoregressive moving average (ARMA); (2) numeric time-series models have been presented to deal with forecasting problems for stock markets, but they can not handle the nonlinear relationships within the stock prices.To address these shortcomings, this paper proposes a new time series model, which employs the ordered weighted averaging (OWA) operator to fuse high-order data into the aggregated values of single attributes, a fusion adaptive network-based fuzzy inference system (ANFIS) procedure, for forecasting stock price in Taiwanese stock markets.In verification, this paper employs a seven-year period of the TAIEX stock index, from 1997 to 2003, as experimental datasets and the root mean square error (RMSE) as evaluation criterion. The experimental results indicate that the proposed model is superior to the listing methods in terms of root mean squared error.     

The Price Relevance of Fiscal Developments

We use Seemingly Unrelated Regressions Estimation methods to assess the link between prices, bond yields and the fiscal behavior. A first equation determines the country-specific cost of government financing via the long-term government bond yield, as a function of budget balance positions. A second equation links the price level to the cost of government financing. Our results for 15 EU countries in the period 1980Q1–2013Q4 show that improvements in the fiscal stance lead to persistent falls in sovereign yields; higher sovereign yields are reflected in upward price movements; improvements in the fiscal stance in recession times lead to short-term decreases in yields and better fiscal stance in expansions induce downward movement in bond yields only after 8 quarters.     

Economic policy uncertainty,financial markets and probability of US recessions

We use probit recession forecasting models to assess the ability of economic policy uncertainty indexes developed by Baker et al. (2013) to predict future US recessions. The model specifications include policy indexes on their own, and in combination with financial variables, such as interest rate spreads, stock returns and stock market volatility. Both in-sample and out-of-sample analysis suggests that the policy uncertainty indexes are statistically and economically significant in forecasting recessions at the horizons beyond five quarters. The index based on newspaper reports emerges as the best predictor, outperforming the term spread at the longer forecast horizons.     

Non linear and asymmetric linkages between real growth in the Euro area and global financial market conditions: New evidence

This paper deals with transition mechanisms through which financial market conditions affect real economic growth in the Euro area. The informational content of financial variables for predicting real economic growth is assessed, allowing for asymmetric responses to shocks. A nonlinear framework is developed based on a smooth transition model for which the effects of shocks can vary across business cycles when financial indicators modify both the endogenous and state variables. Global financial variables are shown to significantly affect real growth in the Euro area, particularly during periods of recession. Changes in stock market index and yield slope have asymmetric effects on real growth. In recessionary periods, the slope of the US yield curve does not have a significant impact on growth in the Euro area.     

Corporate yield curves as predictors of future economic and financial indicators

The government yield curve is known for its ability to predict the future growth rate of the economy. Later studies showed that credit spreads can assist in predicting macroeconomic behaviour as well. We extend this notion by utilizing corporate yield curves and demonstrating that corporate yield curve spreads can predict future economic growth, the future state of the economy and stock market behaviour. In addition, our sample covers the most recent data available, and it also includes the crash year of 2008 and the recovery period following it. Our results reveal a trade-off effect between the government yield curve, which is a better predictor for long-term forecasting, and the corporate yield curves, which are better predictors for short-term predictions. In addition, we show that both the government and corporate yield curves are more effective in predicting negative rather than positive economic changes.     

基于LASSO变量选择方法的投资组合及实证分析

由于传统的Markowitz均值方差模型具有很强的不稳定性,且容易产生较大的空头头寸,因此,资产选择成为构建投资组合的一个研究热点。针对以风险分散和指数跟踪为目的的资产组合构建提出了基于变量选择观点的LASSO选择方法,说明了LASSO方法在资产选择中的优势,并应用LASSO方法使用2010年3月到2012年2月的日收益率数据对沪深300指数的指数跟踪做了实证检验,结果表明LASSO方法在组合构建和预测中都有很好的效果。     

Environmental policy in the European Union: Fostering the development of pollution havens?

A pollution haven occurs when dirty industries from developed nations relocate to developing nations in order to avoid strict environmental standards or developed nations imports of dirty industries expand replacing domestic production. The purpose of this study is to determine whether the European Union (EU) has increased its imports of “dirty” goods from poorer, less democratic countries during a period of more stringent environmental standards. Previous empirical studies such as those by Levinson and Taylor [Levinson, A., and Taylor, M.S., in press. Unmasking the Pollution Haven Effect. International Economic Review.], Ederington, Levinson and Minier [Ederington, J., Levinson, A., and Minier, J., 2005. Footloose and Pollution-Free. Review of Economics and Statistics., 87: 92-99.], Kahn and Yoshino (2004), and Ederington and Minier [Ederington, J., and Minier. J., 2003. Is Environmental Policy a Secondary Trade Barrier? An Empirical Analysis. Canadian Journal of Economics., 36: 137-54.] find evidence that United States imports are responsive to changes in environmental stringency, but the effects of EU policy have not been examined as thoroughly. Our study follows Kahn [Kahn, M.E., 2003. The Geography of Us Pollution Intensive Trade: Evidence from 1958 to 1994. Regional Science and Urban Economics., 33: 383-400.] and examines the impact of industry energy intensity and toxicity, measured by an energy index and a Toxic Release Inventory (TRI) index, on imports into the EU, at the 2-digit industry level from 1970 to 1999. We use the signing of the Maastricht Treaty to signify a period of more uniform and stringent community wide environmental standards (1993-1999), and identify the level of per capita GDP within an EU trading partner. We find an increased amount of EU energy intensive trade with poorer countries during the period with more stringent EU environmental standards. This result is not robust, however, when poorer countries are defined by OECD membership and geographic region. We do not find an increased amount of EU toxic intensive trade with poorer countries although there is some evidence of increased EU imports of toxic goods from poorer OECD and non-EU European countries. For our full sample of trading partners in all regions, the evidence supports the PHH for EU energy intensive trade, but not for toxic intensive trade. Results for regional trade analysis are less clear.     

EU Emission Allowances and the stock market: Evidence from the electricity industry

This paper constitutes - to our best knowledge - the first econometric analysis on stock market effects of the EU Emission Trading Scheme (EU ETS). Our results suggest that EU Emission Allowance (EUA) price developments matter to the stock performance of electricity firms: EUA price changes and stock returns of the most important European electricity corporations are shown to be positively related. This effect does not work asymmetrically, so that stock markets do not seem to react differently to EUA appreciations in comparison to depreciations. The carbon market effect is shown to be both time- and country-specific: It is particularly strong for the period of EUA market shock in early 2006, and differs with respect to the countries where the electricity corporations analysed are headquartered. Stock market reactions to EUA volatility could not be shown.     

Industry-level emission trading between power producers in the EU

This paper investigates how restrictions for emission trading to the energy-intensive power sector will affect the magnitude and distribution of abatement costs across EU countries vis-à-vis a comprehensive EU emission trading regime. It is found that emission trading between European power sectors allows the harvest of a major part of the efficiency gains provided by full trade as compared to strictly domestic action. However, trade restrictions may create a more unequal distribution of abatement costs across member states than is the case for a comprehensive trade regime. The reason for this is that restricted permit trade enhances secondary terms-of-trade benefits to EU member countries with low marginal abatement costs at the expense of the other EU member states.