Key Macroeconomic Variables Research Articles

Business Cycles Dating for EU Economies: An Empirical Search for the Optimal Settings

This paper investigates the estimation of turning points in the business cycles of six major EU economies and the EA. The core dating algorithm as implemented by King and Plosser (1994) is used here and it sheds some more light in the recent financial crisis. We are particularly concerned with the applied researcher's problem of choosing the optimal dating parameters settings for identifying recessions. Our empirical analysis using four key macroeconomic variables suggests the use of 5 phase periods for quarterly and 15 phase periods for monthly data.

The Susceptibility of Islamic Banks' Credit Risk towards Macroeconomic Variables

Credit risk is the most anticipated risk in the banking system. It is one of the key elements to assess systemic risk and stress testing financial fragility which is very helpful to come up with macro-prudential surveillance in financial systems. Unlike the conventional banking system, there is dearth of empirical study on macro-credit risk in relation with Islamic banking. As such, further research regarding the stability of the Islamic banking industry has become imperative. Accordingly, this paper is aimed at determining and assessing the long run vulnerabilities of Islamic financing sustainability in term of its response to changes in key macroeconomic variables by using time series econometric approaches of cointegration and vector autoregression (VAR). Based on the result of simulating variance decomposition (VD) and impulse response function (IRF), it is found that, sufficient evidence of long-run relationship between credit risk ratio in Islamic banking industry and the selected macroeconomic variables exist. The exchange rate, supply side-inflation, and growth have been indicated to negatively influence credit risk rate in Islamic banking, while money supply and Islamic interbank money market rate positively affect the risk rate. © 2014 IIUM Institute of Islamic Banking and Finance.

Stock Market Performance and Macroeconomic Factors: The Study of Indian Equity Market

There has been an extensive debate on the relationship between real economy and stock market performance especially in the context of emerging markets. This article examines the causal relationships between the stock market performance and select macroeconomic variables in India, using monthly data from July 1997 to June 2011. We use factor analysis, ADF and PP Unit root tests, Regression, ARCH model, Granger causality and Johansen Co-integration test for data analysis. Impulse Response analysis has also been performed to check the response of stock market to shocks created in the real economy. We find a significant correlation among stock market indicators and macroeconomic factors. We identified three principal factors through Factor analysis viz Inflation, Interest rate and Exchange rate. The overall explanatory power of the regression model is 23.8%, 23.3% and 16.9% respectively for Sensex, Market capitalization and Market Turnover. There is uni directional causality from stock market to real economy. We find five co-integrating relationships between stock market and macro-economic variables. These results suggest that the stock prices movement is not only the result of behaviour of key macroeconomic variables but it is also one of the important reasons of movement in other macro dimension in the economy.

Forecasting EU Economic Activity Using Financial Condition Indexes

This paper investigates the performance of Financial Condition Indexes (FCIs) in forecasting four key macroeconomic variables of EU economies. A wide range of carefully selected financial indicators include Rates and Spreads, Stock Market Indicators and Macroeconomic Quantities. The results provide evidence that FCIs are particularly useful in forecasting GDP growth, Consumption growth, Industrial Production growth and the Unemployment Rate.

Variable Selection for Large Unbalanced Datasets Using Non-Standard Optimisation of Information Criteria and Variable Reduction Methods

We consider forecasting key macroeconomic variables using many predictors extracted from the Eurostat PEEIs dataset. To avoid the curse of dimensionality, we rely on model selection and model reduction. For model selection we use heuristic optimisation of information criteria, including simulated annealing, genetic algorithms, MC^3 and sequential testing. For model reduction we employ the methods of principal components, partial least squares and Bayesian shrinkage regression. The problem of unbalanced datasets is discussed and potential solutions are suggested. We provide adequate evidence that these methods could be useful in forecasting. Their predictive performance is evaluated in a pseudo out-of-sample exercise, comparing the results relative to a univariate AR(1) benchmark. Our findings are very encouraging for forecasting the growth rate of quarterly consumption and GDP, and monthly industrial production and inflation.

Foreign interest rate shocks and exchange rate regimes in East Asia

Using a theoretical dynamic stochastic general equilibrium model and an empirical panel vector autoregression, we assess the transmission of foreign real interest rate shocks on the volatility of various key macroeconomic variables in nine small open economies in East Asia taking into account the role of exchange rate regimes. Both the theoretical and empirical findings confirm the hypothesis that flexible exchange rate may work as a shock absorber when the economy is hit by foreign real interest rate shocks. The findings suggest a clear trade-off between the volatility of real exchange rate and real output to foreign interest rate shocks, both the US and G7 real interest rates, where the responses of real output are mitigated in countries that have more flexible exchange rate regime.

Inflation in the Great Recession and New Keynesian Models

Several prominent economists have argued that existing DSGE models cannot properly account for the evolution of key macroeconomic variables during and following the recent Great Recession. We challenge this argument by showing that a standard DSGE model with financial frictions available prior to the recent crisis successfully predicts a sharp contraction in economic activity along with a protracted but relatively modest decline in inflation, following the rise in financial stress in 2008:IV. The model does so even though inflation remains very dependent on the evolution of economic activity and of monetary policy. (JEL E12, E31, E32, E37, E44, E52, G01)

Bubbles over the U.S. business cycle: A macroeconometric approach

This paper builds a New Keynesian model with financial frictions and monetary and fiscal rules for the United States. We incorporate a rational bubble process in the (relative) price of capital. Our results show that bubbles account for a significant amount of variance in key macroeconomic variables and are as important as investment-specific shocks in explaining total variation. Further, we show that a bursting bubble creates large and long-lasting real effects. In particular, we find large effects on government debt that persist for several years.

Credit supply shocks and the global financial crisis in three small open economies

We investigate the impact of domestic and foreign credit supply shocks on a number of key macroeconomic variables for three small open economies: Australia, Canada and the UK. We find that negative domestic and foreign credit supply shocks together explain, on average, one-third to one-half of the fall in business credit and rise in spreads seen in the three countries during the financial crisis; other identified non-credit-supply shocks explain the rest. Credit supply shocks also explain around one-sixth of the fall in output in the three countries, and one-quarter of the fall initially seen in UK inflation. This suggests that credit supply shocks played an important role in the financial crisis, but not a dominant one.

Alternative Models for Forecasting the Key Macroeconomic Variables in Armenia

This paper uses three well known forecasting models, particularly unrestricted VAR, Bayesian VAR and Factor Augmented VAR. These models we use for forecasting the key macroeconomic variables in Armenia (real growth of GDP, inflation and nominal short-term interest rate). We apply three models to the Armenian economy using quarterly macroeconomic time series from 2000 to 2012. The main purpose of the current paper is to compare various forecasting models, in order to find that model which is more appropriate for forecasting Armenian’s key macroeconomic variables. In order to answer this question we conduct out of sample forecast experiments. Based on the out of sample forecast experiments and using forecast evaluation RMSE (the Root Mean Squared Error) criteria we make comparisons between small scale (VAR, BVAR) and large scale (FAVAR) models.

What Happens after the Central Bank of Brazil Increases the Target Interbank Rate by 1%?

I start presenting an explicit solution to Tayloris (2001) model, in order to illustrate the link between the target interest rate and the overnight interest rate prevailing in the economy. Next, I use Vector Auto Regressions to shed some light on the evolution of key macroeconomic variables after the Central Bank of Brazil increases the target interest rate by 1%. Point estimates show a four-year accumulated output loss ranging from 0:04% (whole sample, 1980: 1-2004: 2; quarterly data) to 0:25% (Post-Real data only) with a first-year peak output response between 0:04% and 1:0%; respectively. Prices decline between 2% and 4% in a 4-year horizon. The accumulated output response is found to be between 3:5 and 6 times higher after the Real Plan than when the whole sample is considered. The 95% confidence bands obtained using bias-corrected bootstrap always include the null output response when the whole sample is used, but not when the data is restricted to the Post-Real period. Innovations to interest rates explain between 4:9% (whole sample) and 9:2% (post-Real sample) of the forecast error of GDP.

The Effects of Oil Price Volatility on the Sudanese Economy

After the oil exploitation in 1999, Sudan has relied primarily on oil revenues, which rendered its economy highly vulnerable to the international oil price shocks. This study examines the dynamic impact of crude oil price fluctuations on the key macroeconomic variables in Sudan, using quarterly data over 1999:Q4–2009:Q4. The study employs impulse response functions and variance decompositions techniques based on unrestricted the vector autoregressive approach. The empirical results reveal that oil price shocks have significant effects on the main macroeconomic variables such as, real GDP, inflation and exchange rate. Moreover, the study found an evidence of asymmetry relationship between oil prices changes and macro variables.

Investment shocks and consumption

Several influential papers have argued that preferences featuring a weak wealth effect on labour supply are key to generate macroeconomic co-movement across real variables in response to shocks. Using a fully general specification for the instantaneous utility function, we show that the size of the wealth effect on labour supply is largely inconsequential for macroeconomic dynamics. Instead, we find that Edgeworth complementarity between consumption and hours worked is crucial in order to obtain co-movement of key macroeconomic variables. We consider investment shocks and we show that co-movement can easily be achieved with non-separable preferences in combination with a reasonable degree of nominal rigidity. This holds even in the presence of sizeable wealth effects.

Oil shocks and monetary policy rules in emerging economies

We examine the effects of shocks in the oil market on key macroeconomic variables in small open economies using a dynamic stochastic general equilibrium model with sticky prices and imperfect competition under different monetary policy rules. The numerical solutions show that the types of exchange rate regimes and monetary policies could partly explain the trends in macroeconomic volatilities considering negative shocks to oil supply (Hamilton, 1983) and positive shocks to oil demand (Kilian, 2009). These findings are confirmed in vector autoregressive responses for Chile and Israel with inflation targeting under flexible exchange regimes and Hong Kong with fixed regime.

An Overview of the Repo Rate in an Inflation Targeting Economy

AbstractThis paper compares the use of repo rate in South Africa during the pre‐repo and repo system by trending and comparing the interest rate fluctuations between two selected periods of 1990–1998 and 1998–2010. Using a structural vector autoregressive (SVAR) econometric method to determine the relationship between the repo rate and other selected key macroeconomic variables in South Africa, an improved monetary efficiency was found during the repo period, which can be attributed to the use of an inflation‐targeting framework. This is important as it provides a guide to policymakers on how effective the current monetary tool is, and how efficient the South African Reserve Bank (SARB) is in influencing the interbank rate, retail rates and inflation during selective periods.

Applying a macro-finance yield curve to UK quantitative Easing

We estimate a macro-finance yield curve model for both the nominal and real forward curve for the UK from 1993 to 2008. Our model is able to accommodate a number of key macroeconomic variables and allows us to estimate the instantaneous response of the yield curve and so gauge the impact of Quantitative Easing on forward rates. We find that 10year nominal interest rates on average are lower by 46 basis points which can largely be explained by three main channels: portfolio balance; liquidity premium and signalling but there is no sizeable impact on real interest rates.

Yield spread as a leading indicator of Tunisian industrial production

Can the yield spread, which has been found to predict with surprising accuracy the movement of key macroeconomic variables of developed countries, also predict such variables for an emerging country. This paper is an attempt to answer empirically this question for the Tunisian economy. It also examines international financial linkages and how the euro area yield curve helps to predict domestic macro financial variables. Although the phenomenon has been widely examined in developed market economies, similar studies are virtually absent in the case of emerging economies. In part, this is because in developing economies with administrated interest rates, the yield curve has been either completely absent or not market determined and thus did not form a suitable test case. In the Tunisian financial market, there has been considerable improvement in terms of volumes, variety of instruments, numbers of participants and dissemination of information, and a yield curve particularly in case of government securities started emerging since 2000. In our study, two approaches are implemented. The first one, widely used, consists in regressing the growth rate of the coincident indicator on the leading indicator. In the second one, we examine the usefulness of the yield spread in predicting whether or not the economy will be in recession in the future. So, in that particular case we use a Probit model. For both approaches we use the in-sample forecasting ability as well as the out-of-sample accuracy of the outcomes. The results are somewhat tentative but consistent with the similar studies conducted in case of other countries. Findings of the study provide evidence that the yield curve could be considered as a leading indicator of real growth or recessions in Tunisian context, and consequently may be useful for both to private investors and to policy makes for forecasting purposes and, perhaps more importantly to understand the ongoing process of international financial integration.

Forecasting Inflation In China

China is the worlds second largest economy, has sustained strong growth rates for an extended period of time, and is a prime destination for international investors. It is therefore important for researchers to correctly forecast key macroeconomic variables, such as economic growth and inflation within the Chinese economy. Forecasts of inflation, in particular, are important for domestic production, export competitiveness, business planning and for international investors. A section of the literature has assessed models to explain and forecast inflation within this literature, the role of deviations of output from equilibrium output (Phillips Curve models specified as output gap models) and the role of monetary policy in explaining inflation in China have been of great interest. This paper assesses atheoretic and structural models to explain Chinese inflation and tests the forecasting ability of these models. The findings show that money is not as important in explaining inflation as the output gap. The output gap approach also provides the best forecasts of inflation for the out-of-sample period 2003-2012. Models based on past information alone cannot beat the output gap models.

1979–2001: A Greek great depression through the lens of neoclassical growth theory

This paper focuses on the performance of the Greek economy during the period 1979–2001. Following the work of Cole and Ohanian (1999) and Kehoe and Prescott (2002, 2007) this twenty year episode can be characterized as a great depression. We use this methodology and ask whether, given the observed exogenous path of total factor productivity (TFP), the neoclassical growth model can generate an equilibrium behavior that has growth accounting characteristics similar to those in the data. The answer is affirmative: Changes in TFP are crucial in accounting for the Greek great depression. Our model economy predicts a big decline of economic activity during the 80s and until the mid-90s and a strong recovery for the period 1995–2001. This is exactly what happened in Greece. Moreover, the model successfully mimics the actual data with respect to the timing of peaks and troughs and the time paths of most key macroeconomic variables. However, puzzles between theory's predictions and the observed data are not missing. For instance, things are (not surprisingly for the neoclassical growth model) less successful when it comes to the labor factor.

The political economy of Iraq: restoring balance in a post-conflict society

Contents: Preface 1. Iraq's Lost Decades 2. Population and Key Macroeconomic Variables 3. Health, Poverty and Education 4. Corruption 5. Political Stability and Economic Development 6. Oil and Gas 7. Agriculture and the Public Distribution System 8. Financial Intermediation 9. State Owned Enterprises 10. Entrepreneurship in Post-conflict Iraq 11. Infrastructure and Essential Services 12. International Trade and Finance 13. Fiscal, Monetary and Exchange Rate Policy 14. Iraq in 2025 Bibliography Index