Local and global indeterminacy in two-sector models of endogenous growth

We consider a two-sector endogenous growth model where the productions of the final good and human capital require economy-wide external effects. Assuming constant returns to scale at the private and social levels, we show that local and global indeterminacy of equilibrium paths are compatible with any values for the elasticity of intertemporal substitution in consumption and any sign for the capital intensity difference across the two sectors. We also show that for any value of the elasticity of intertemporal substitution in consumption, poverty traps may occur when the final good sector is capital intensive in human capital.     

Monetary policy and asset prices in an open economy

This paper examines whether central banks should respond to asset price fluctuations in a two-country sticky price model. We compare a monetary policy rule that targets both domestic asset prices and foreign asset prices with several alternative monetary policy rules. This paper shows that this policy rule can produce preferable outcomes because the domestic central bank incorporates important information that both domestic and foreign asset prices possess into its monetary policy. Our model suggests that central banks should consider both domestic and foreign asset prices in a two country framework with asset price fluctuations.     

Active intermediation in a monetary overlapping generations economy

This paper establishes that the profit-seeking activities of private intermediaries can ensure Pareto efficiency in the standard pure-exchange monetary overlapping generations economy without the need for government monetary or fiscal policy intervention. Moreover, these profit-seeking activities are shown to rule out all aperiodic and k-periodic cycles for k greater than 2. Contrary to much recent work on intermediation, the profit opportunities that arise for intermediaries in this context are not due to assumed frictions or asymmetric information. Rather, they are due to the dynamic open-ended structure of the economy, which permits debt roll-over.     

Foreign and domestic growth drivers in Eastern Europe

This paper analyses the growth effects of capital formation, exports and FDI as major, drivers of economic development in Eastern Europe. The fundamental innovations are, identified by empirically and theoretically motivated short- and long-run restrictions in, structural cointegrated vector autoregressions. Impulse responses and variance, decompositions reveal quite different growth effects in various Eastern European countries. Generally, a strong reliance on exports goes along with higher GDP, and FDI bears, substantial potential for fostering economic growth. It is shown that the recent worldwide, recession clearly hit Eastern Europe through the export channel, whereas the recovery is, mainly supported by positive demand shocks.     

Financial reforms and money demand: Evidence from 20 developing countries

The effects of financial reforms on money demand (M1) are analysed with estimates for two sets of sub-samples and two break dates for twenty developing Asian and African countries. In all cases, the magnitude of income elasticity does not change significantly when compared with sub-samples and whole sample periods. Using CUSUM and CUSUMSQ tests, we find that the demand for money functions in our selected countries are temporally stable and therefore the respective monetary authorities may target money supply as the conduct of monetary policy.     

A bootstrap algorithm for testing cointegration rank in VAR models in the presence of stationary variables

In this paper, a bootstrap algorithm for a reduced rank vector autoregressive (VAR) model which also includes stationary regressors, is analyzed. It is shown that the bootstrap distribution for estimating the rank converges to the distribution derived from the usual asymptotic framework. Because the asymptotic distribution will typically depend on unknown parameters, bootstrap distributions are of considerable interest in this context. The result of an application and some Monte Carlo experiments are also presented.     

Bayesian inference in a time varying cointegration model

There are both theoretical and empirical reasons for believing that the parameters of macroeconomic models may vary over time. However, work with time-varying parameter models has largely involved vector autoregressions (VARs), ignoring cointegration. This is despite the fact that cointegration plays an important role in informing macroeconomists on a range of issues. In this paper, we develop a new time varying parameter model which permits cointegration. We use a specification which allows for the cointegrating space to evolve over time in a manner comparable to the random walk variation used with TVP–VARs. The properties of our approach are investigated before developing a method of posterior simulation. We use our methods in an empirical investigation involving the Fisher effect.     

Growth, development and natural resources: New evidence using a heterogeneous panel analysis

This paper explores whether natural resource abundance is a curse or a blessing. To do so, we firstly develop a theory consistent econometric model, in which we show that there is a long run relationship between real income, the investment rate, and the real value of oil production. Secondly, we investigate the long-run (level) impacts of natural resource abundance on domestic output as well as the short-run (growth) effects. Thirdly, we explicitly recognize that there is a substantial cross-sectional dependence and cross-country heterogeneity in our sample, which covers 53 oil exporting and importing countries with very different historical and institutional backgrounds, and adopt the non-stationary panel methodologies developed by Pesaran (2006) and Pedroni (2000) for estimation. Our results, using the real value of oil production, rent or reserves as a proxy for resource endowment, reveal that oil abundance has a positive effect on both income levels and economic growth. While we accept that oil rich countries could benefit more from their natural wealth by adopting growth and welfare enhancing policies and institutions, we challenge the common view that oil abundance affects economic growth negatively.     

Asymmetric Taylor reaction functions of the ECB: An approach depending on the state of the economy

We introduce a new approach to estimate asymmetric Taylor reaction functions where asymmetries depend crucially on the state of the economy which is in the Taylor rule framework the combination of inflation and output deviations. Thus we categorize the sample into four subsamples which correspond to all possible combinations concerning inflation and output deviations. Moreover we introduce a quadratic term of inflation and the output gap in the estimation equation for each state in order to capture possible non-linearities within each state. The approach is tested using data for the ECB because the ECB has communicated an explicit inflation target.     

P-star in times of crisis – Forecasting inflation for the euro area

In this paper we present three empirically testable versions of the common p-star model and evaluate their forecasting performance using conventional techniques. We try to answer the question if the p-star approach is preferable to achieve a reliable short-run inflation forecast and with regard to the latter we incur the need for a stable demand for money function. Our findings indicate the recurrence of the relevance of the monetary pillar of the ECB's two-pillar framework. In addition, we check for the effects of the current financial and economic crisis that started in 2007 on the forecasting performance, using two sub-sample periods, one excluding and one including the latter, and analyze the impact of the applied filter technique to compute the required equilibrium values.     

Volatility contagion: A range-based volatility approach

This article proposes a new approach to evaluate volatility contagion in financial markets. A time-varying logarithmic conditional autoregressive range model with the lognormal distribution (TVLCARR) is proposed to capture the possible smooth transition in the range process. Additionally, a smooth transition copula function is employed to detect the volatility contagion between financial markets. The approach proposed is applied to the stock markets of the G7 countries to investigate the volatility contagion due to the subprime mortgage crisis. Empirical evidence shows that volatility is contagious from the US market to several markets examined.     

Booms and busts in housing markets: Determinants and implications

This study looks at the characteristics and determinants of booms and busts in housing prices for a sample of eighteen industrialised countries over the period 1980–2007. From an historical perspective, we find that recent housing booms have been amongst the longest in the past four decades. Estimates of a Multinomial Probit model suggest that domestic credit and interest rates have a significant influence on the probability of booms and busts occurring. Moreover, international liquidity plays a significant role for the occurrence of housing booms and—in conjunction with banking crises—for busts. We also find that the deregulation of financial markets has strongly magnified the impact of the domestic financial sector on the occurrence of booms.     

Does money help predict inflation? An empirical assessment for Central Europe

This paper investigates the predictive ability of money for future inflation in the Czech Republic, Hungary, Poland and Slovakia. We construct monetary indicators similar to those the European Central Bank regularly uses for monetary analysis. We find in-sample evidence that money matters for future inflation at the policy horizons that central banks typically focus on, but our pseudo out-of-sample forecasting exercise shows that money does not in general improve the inflation forecasts vis-à-vis some benchmark models such as the autoregressive process. Since at least some models containing money improve the inflation forecasts in certain periods, we argue that money still serves as a useful cross-check for monetary policy analysis.     

The exchange rate and macroeconomic determinants: Time-varying transitional dynamics

In this paper, I consider modeling the effects of the macroeconomic determinants on the nominal exchange rate to be channeled through the transition probabilities in a Markovian process. The model posits that the deviation of the exchange rate from its fundamental value alters the market's belief in the probability of the process staying in certain regime next period. This paper further takes into account the ARCH effects of the volatility of the exchange rate. Empirical results generally confirm that fundamentals can affect the evolution of the dynamics of the exchange rate in a nonlinear way through the transition probabilities. In addition, I find that the volatility of the exchange rate is associated with significant ARCH effects which are subject to regime changes.     

Independent component analysis for realized volatility: Analysis of the stock market crash of 2008

This paper investigates the factors that drove the U.S. equity market returns from 2007 to early 2010. The period was highlighted by volatile energy and commodity prices, the collapse of insurance and banking firms, extreme implied volatility and a subsequent rally in the overall market. To extract the driving factors, we decompose the returns of the S&P500 sector ETFs into statistically independent signals using independent component analysis. We find that the generated factors have interesting financial interpretations and are consistent with the major economic themes of the period. We find that there are two sets of general market betas during the period along with a dominant factor for energy and materials sector. In addition, we find that the EGARCH model which accommodates asymmetric responses between returns and volatility can plausibly fit the high levels of variance during the crash. Finally, estimated correlations dropped when commodity prices moved higher, but then spiked when the S&P500 crashed in late 2008.     

Should the government directly intervene in stock market during a crisis?

Unlike foreign exchange markets where central banks frequently intervene, the governments strive not to intervene in the stock markets since intervention transmit negative signals and carry market-related side effects. The main reasons often cited in support of intervention are to bring price stability and to restore investors’ confidence. During the recent economic turmoil, opportunities for the governments to intervene in the stock markets were mainly exploited in emerging and developing countries. We study the outcome of the Russian government's intervention in its major stock market between September and October 2008. This intervention was intended to reverse the sudden and swift declining trend in traded security prices by altering the market's expectations. By using a combination of event study and a multivariate GARCH model, our findings does not support direct government intervention in the stock market during a crisis.     

Housing, credit, and real activity cycles: Characteristics and comovement

This paper describes the characteristics and comovement of cycles in house prices, residential investment, credit, interest rates, and real activity in advanced economies during the past 25 years. Stylized facts and regularities are uncovered using a dynamic generalized factor model and spectral techniques. House price cycles are found to lead credit and real activity over the long term, while in the short to medium term the relationship varies across countries. Interest rates tend to lag other cycles at all time horizons. Although global factors are important, the US business cycle, housing cycle and interest rate cycle generally lead the respective cycles in other countries over all time horizons, while the US credit cycle leads mainly over the long term.     

Particle filters for continuous likelihood evaluation and maximisation

In this paper, a method is introduced for approximating the likelihood for the unknown parameters of a state space model. The approximation converges to the true likelihood as the simulation size goes to infinity. In addition, the approximating likelihood is continuous as a function of the unknown parameters under rather general conditions. The approach advocated is fast and robust, and it avoids many of the pitfalls associated with current techniques based upon importance sampling. We assess the performance of the method by considering a linear state space model, comparing the results with the Kalman filter, which delivers the true likelihood. We also apply the method to a non-Gaussian state space model, the stochastic volatility model, finding that the approach is efficient and effective. Applications to continuous time finance models and latent panel data models are considered. Two different multivariate approaches are proposed. The neoclassical growth model is considered as an application.