Studying the Neutrality of Money: An Evidence of OPEC Member States

Transcription

1 Available online at ISSN: Studying the Neutrality of Money: An Evidence of OPEC Member States Mohsen Mehrara Faculty of Economics, University of Tehran, Tehran, Iran Sarah Katanchian M.A Student of Economics, Aras International Campus, University of Tehran, Iran Abstract The main fundamental issue in developing oil exporting countries is that there is a disagreement between monetary policy makers and producers. Producers claim that the contraction of monetary policies reduces the output. In contrary with this, policymakers claim that the problem is low efficiency of producers. This paper studies the neutrality of money in OPEC member countries using panel approach during the period Gross domestic product, liquidity, oil price, exchange rate, gross fixed capital formation and consumer price index are variables which were used in this investigation. The results of this research implied that there is a negative and significant relationship between liquidity and economic growth. A positive and significant relationship between inflation and economic growth is also founded. The results support that money is not neutral in mentioned countries. So, economists and policy makers ought to use appropriate monetary policies for reducing macroeconomic volatilities. JEL Classification: E4, E5 Keywords: Gross Domestic Product, Liquidity, Neutrality of Money, Oil Price, Organization of the Petroleum Exporting Countries. 1. Introduction A popular field of debate in Economics literature is the neutrality of money in oil exporting countries (OPEC 1 members). A clear understanding of the relationship between these variables is important, especially to the policymakers to guarantee effectiveness of macroeconomic stabilization policies. Money and liquidity have low influence on real economic variables in these countries. However, they have dramatically influenced nominal economic variables. Policymakers use monetary policies for controlling quantity of output. However, it might cause inflation. Hence, using or not using monetary policies is a well-known field of debates between economists. These facts guided to an expanding number of researches studying neutrality of money in oil exporting countries. Some of them believe in money neutrality and some do not. Some theories are represented about effectiveness of monetary policy in short-run by monetarists. On the other hand, real business cyclists, in contrary with monetarists, believe that money is neutral in short- and long-run (Abbasinejad, 2006). Classics believe that money is neutral in long-run and it s movements do not have any effects on real economic sector. They separated nominal and real sectors of economy and overall they believe in neutrality of monetary policies (Snowdon and Wynareczyk, 1994). Real business cyclists believe in neutrality of money in short-run and also long-run and there is a positive correlation between money and output. It means that money has influenced output. They believe that money demand increased in prosperity condition and it is with positive responses from money supply, particularly if policymakers used exchange rate targeting. Literman and Weiss (1985); Barro (1993) and Sims (1980, 1983) give some evidence in order to support real business cycle that indicates their tendency for non-monetary approach for modeling business cycle. In this paper, we are going to study neutrality of money in oil exporting countries which are member of OPEC. Unlike the previous individual-country level researches, according to the authors' knowledge, this paper is one of the rare 1 Organization of the Petroleum Exporting Countries 1

2 Studying the Neutrality of Money: An Evidence of OPEC Member States Mohsen Mehrara, Sarah Katanchian studies in this subject. Lack of data is one of the main causes of scarcity of studies in this field. Panel approach allows us to pool large number of observations from small number of countries and get more accurate results (Mehrara and Mohagheghç 2011).We will study the macroeconomic dynamics between economic output (GDP), domestic price level (CPI), money supply (M2) as a % of GDP, real effective exchange rate (ER), gross fixed capital formation (GFCF) as a % of GDP and oil price over a group of main oil exporting countries which are OPEC members. A panel approach is used for estimating the nexus between these variables. Our sample covers data from 1960 to 2013 in all OPEC member states, namely Algeria, Angola, Ecuador, Iran, Iraq, Kuwait, Nigeria, Qatar, Saudi Arabia, The United Arab Emirates and Venezuela. This paper organized in 5 sections. In section 2, a brief review of literature on the neutrality of money in oil exporting countries is presented. Section 3, introduces the data and methodology. Section 4 reports empirical findings and finally, section 5 concludes the paper. 2. Literature review Studying the role of oil price in macroeconomic dynamics came in to the focal point of researches since 1970s. Here, we review the related literature regarding in neutrality of money. Blanchard and Quah (1989) want to investigate effects of dynamic movements of demand and supply on output and unemployment rate in America during 1950 to They used a VAR model indicating that variance decomposition has dramatic standard deviation. Demand disturbances in output fluctuations are greatly affected by trend and structural break. Demand disturbances in short-run are improved. However, demand and supply disturbances in unemployment fluctuations are not influenced by trend and structural break. Altogether, demand shocks have more impact on unemployment fluctuations. Cover (1992) evaluates the effects of monetary shocks on real economic variables in the United States of America. The results indicated that negative monetary shocks have significant effects on real output. However, positive monetary shocks have not any significant effects on real output and also negative shocks have more effects on real output that positive ones. Kireyev (2000) using the mean-group estimator in a PVAR approach, analyzed the effects of both internal shocks on macroeconomic movements in 18 Arab countries. Kireyev (2000) compare growth performance, fiscal and current account developments in these countries. Bonato (2007) estimates the relationship between nominal variables and inflation in Iran. This paper answered questions about decline in inflation which took place at the first half of The outcome implies that there is a strong relationship between money and inflation when M1 is used with no proof of a structural change. Mehrara and Mohaghegh (2011) focus on developing net oil exporters (unlike with most other studies which focuses on developing net importers) and investigate macroeconomic fluctuations, supplying fresh penetration into the impacts of oil shocks on macroeconomic variables. Their findings indicate that money is not neutral in mentioned countries. Lashkary and Kashani (2011) investigate the neutrality or non-neutrality of the money in Iran during the period 1959 to This study has been investigated by the monetarists approach and analyzes events by experimental observation in several statistical models. The results showed that there is not any significant relationship between money volume and real economic variables, production and employment. There is not any intensive fluctuation in gross domestic products in Iran except in recent years and it has a normal direction. However, there is a large fluctuation which is not natural in unemployment rate. Boyoiyour and Selmi (2013) study the relationship between real oil price and real effective exchange rate in three GCC countries namely Qatar, Saudi Arabia and United Arab Emirates. This study has been investigated by employment of wavelet decomposition and nonlinear causality test. The results showed that Qatar and UAE should improve the downward effect of oil price on real exchange rate by amending diversification policy and also they implied that the behavior of Saudi Arabia as a price maker may let it to keep a fast recovery under oil shocks. Damette and Seghir (2014) empirically investigate dynamic relationship in 12 oil exporting countries between two variables during 1990 to This research has been investigated by recently developed panel econometric techniques. This paper accounts for cross-section dependence when analyzing the energy income nexus. The observation outcome means that there is a long-run equilibrium relationship between energy consumption and economic growth. Moreover, the result of a dynamic panel error correction model reveals a short run unidirectional causality from energy consumption to economic growth. But, in the long-run, it is the economic process that determines in energy consumption trend. Alavinasab (2014) investigates the factors affecting the rate of inflation in Iran. In this paper, augmented Dickey Fuller (ADF) test used for determining the existence of unit root and also stationary of the series. Moreover, Johansen cointegration test is used for evaluating the existence of long-run relationship among the series and also for capturing the convergence of the inflation determining factors for achieving long-run equilibrium. An error correction mechanism (ECM) is also used. The results showed that there is a long-run nexus among variables of money supply, gross domestic 2

3 product, oil export revenue, and inflation. Findings of ECM implies short-run equilibrium happen to equalize the model in long-run. 3. Data and Methodology In this section, for the sake of estimating neutrality of money in oil exporting countries, we concentrate on these 12 countries: Algeria, Angola, Ecuador, United Arab Emirates, Iran, Iraq, Kuwait, Libya, Nigeria, Qatar, Saudi Arabia and Venezuela during the period In an unbalanced Panel framework, our variables which were involved in this paper are logarithm of gross domestic product (GDP), money supply (M2) as a % of GDP, logarithm of consumer price index (CPI), real effective exchange rate (ER), gross fixed capital formation (GFCF) as a % of GDP and yearly average of crude oil price (OILP). The whole data obtained from World Development Indicators (WDI) s online database. Using logarithm forms can trim down the problem of heterosckedasticity (Gujarati, 2004). Thus, in this model, we use logarithmic form of our variables which are not % of GDP themselves. Since most of empirical studies in the subject of neutrality of money use non-stationary in levels, it is fundamental to examine for unit roots, co-integration and cross-section dependence for avoiding spurious results. Existence of unit root test in panel data like time series led to spurious regression. Hence, testing for unit root tests has become an standard procedure not also in time series but also in panel data analyzes. Panel unit root tests have been declared by Levin, Lin and Chu (1992); Im, Pesaran and Shin (1997); Harris and Tzavalis (1999); Madala and Win (1999). Panel co-integration tests can be motivated by the search for more powerful tests than those obtained by applying individual time series co-integration tests. Pedroni (1999, 2004) proposed several tests for the null hypothesis of cointegration in a panel data model that allows for considerable heterogeneity. Based on a panel approach our modified model is specified as below: D(log(GDP)) it=ß 0+ß 1D(M2) it+ß 2D(log(CPI)) it+ß 3D(ER) it+ß 4(GFCF) it+ß 5 D(oilprice) it+u it Equation (1) Where: i represents countries and t represents the year and u is stochastic error term. D implies the first difference. log (GDP) represents the logarithm of gross domestic product, (M2) represents money and quasi money as a % of GDP, CPI represents consumer price index (2010=100), ER represents official Exchange rate (2010=100), GFCF represents gross fixed capital formation as a % of GDP, oilprice represents yearly average of crude oil price of OPEC members. Gross Domestic Product (GDP) is the value of all final goods and services produced in the economy in a given time period (quarter or year). GDP is the basic measure of economic activity (Dornbusch, 1977). Consumer Price Index (CPI) is the cost of a given basket of goods, representing the rate of increase of prices (Dornbusch, 1977). Money plus Quasi Money (M2) consists of M1 plus savings accounts and small-denomination time deposits plus balances in retail money market mutual funds (Walsh, 2006). M1 consists of currency held by the nonbank public, travel checks, and demand deposits. M 0 is a narrow definition of the money supply, consisting of total reserves held by the banking system plus currency in the hands of the public. Gross Fixed Capital Formation (GFCF) is investments in land improvements (fences, ditches, drains, etc.); plant, machinery, and equipment purchases; and the construction of roads, railways and the like, including commercial and industrial buildings, offices, schools, hospitals and private residential dwellings (Krkoska, 2002 ). Exchange Rate (ER) is an exchange rate between two currencies is the rate at which one currency will be exchanged for another. It is also regarded as the value of the one country s currency in terms of another currency (Sheffrin, 2003). Oil Price is the price of oil, or the oil price, generally refers tosspot price of a barrel of benchmark crude oil. A benchmark crude or marker crude is a crude oil that serves as a reference price for buyer and sellers of crude oil. There are three primary benchmarks, west Texas intermediate (WTI), Brent Blend, and Dubai crude. Benchmarks are used since there are many different varieties and grades of crude oil. Using benchmarks makes referencing types of oil easier for sellers and buyers. (International Crude Oil Market Handbook, 2011) 4. Empirical results In this section, we are going to report the empirical evidence regarding in the model specified in section 3. First of all, the descriptive statistics are calculated and performed for each variable in this section. All the variables have positive mean values and CPI has greater mean, median, maximum and minimum among all variables. Eventually statistics express the highest standard deviation for oil price. 3

4 Studying the Neutrality of Money: An Evidence of OPEC Member States Mohsen Mehrara, Sarah Katanchian Table 1: Descriptive Statistics Variables Mean Median Maximum Minimum Std.Dev. GDP M CPI GFCF OILP ER It is well established that the non-stationarity of the variables in standard OLS regression can cause spurious regression (Granger and Newbold, 1974). Thus, it is important to know if our variables are stationary or not. In this paper, we apply Im, Pesaran and Shin W-stat unit root tests for the panel data. Table (2) indicates the results of unit root tests showing that all variables are non-stationary at level except GFCF. Table 2: Unit Root Test Results Variables LOG(GDP) M2 LOG(CPI) GFCF ER OILP Statistic Prob As it is obvious, our variables are non-stationary at level except GFCF. So, it is necessary to obtain first difference of them. Results of Table (3) indicated that after getting first difference, all of them are stationary. Table 3: Unit Root Test Results after Considering First Difference of Variables. Variables D(LOG(GDP)) D(M2) D(LOG(CPI)) D(ER) D(OILP) Statistic Prob Pedroni residual co-integration test is conducted in Table (4) to analyze the existence of long-run relationship among the variables. As the results imply, all the probability of variables are greater than 5%. Hence, we accept null-hypothesis of no co-integration among these variables at 5%. Thus, there is no co-integration among the variables. Table 4: Pedroni Residual Co-integration Test Statistic Prob. Weighted Statistic Prob. Panel v-statistic Panel rho-statistic Panel PP-Statistic Panel ADF- Statistic Due to the redundant likelihood test results (for choosing best method between pooled and panel), we chose fixed effects method. Table5: Redundant Fixed Effects Test Effects Test Statistic d.f. Prob. Cross-section F (7,50) Table 6: Cross-Section Fixed Effects Variables Coefficient Std. Error t-statistic Prob. C D(M2) D(LOG(CPI)) GFCF D(OILP) D(ER) R-squared Prob(F-statistic) Adjusted R-squared S.E of regression Durbin-Watson stat

5 According to Table 7, Hausman specification test (to choose the best method between fixed and random) indicates that since the probability is greater than 5%, we should use Random Effects. Table 7: Correlated Random Effects-Hausman Test. Test summary Chi-Sq. Statustic Chi-Sq. d.f. Prob. Cross-section random Note: H 0 estimates by Random are not different from those from fixed effects. Random should be accepted. H 1 estimates by Random are not different from those from fixed effects. Random should be rejected. Table 8: Cross-Section Random Effect tests Variables Coefficient Std. Error t-statistic Prob. C D(M2) D(LOG(CPI)) GFCF D(OILP) D(ER) R-squared Prob(F-statistics) Adjusted R-squared S.E of regression Durbin-Watson stat We find that all variables are significant at 5% except inflation which is significant at 10%. As it obvious from results, there is a positive and significant ( ) relationship between economic growth and inflation and also a negative and significant relationship between economic growth and liquidity. By comparing between five effective factors on economic growth, we discover taht the effect of inflation among all factors is the most. The result implies that an increase of 1% in inflation causes 4.5% increase in economic growth and an increase of 1% in liquidity 0.099% decreases economic growth. Findings imply that money is not neutral in mentioned countries. Table 9: Cross-Section Random Effects after Omitting ER. Variables Coefficient Std. Error t-statistic Prob. C D(M2) D(LOG(CPI)) GFCF D(OILP) R-Squard Prob(F-statistic ) Adjusted R-squared S.E of regression Durbon-watson stat Conclusions The main purpose of present study was to investigate neutrality of money in oil exporting countries which is OPEC members namely: Algeria, Angola, Ecuador, United Arab Emirates, Iran, Iraq, Kuwait, Libya, Nigeria, Qatar, Saudi Arabia and Venezuela during the period 1960 to One of the fundamental issues in these counties is that there is a disagreement between monetary policy makers and producers. Producers claim that the contractionary monetary policies reduce the output. In contrary, policymakers argue that the problem is low efficiency of producers. Unit Root Test for investigating stationarity of variables has been used and findings implied that some variables were non stationary in sample. So, first difference of those variables is used. Moreover, co-integration test has been used and showed that there was no co-integration among variables. Hausman test indicated that Random Effect test should be used. Eventually, there was a positive and significant relationship between economic growth and inflation and also a 5

6 Studying the Neutrality of Money: An Evidence of OPEC Member States Mohsen Mehrara, Sarah Katanchian negative and significant relationship between economic growth and liquidity. Findings imply that money is not neutral in these countries. So, any increase in liquidity would affects prices and also it affects Gross Domestic Product. Monetary policies can be used to stimulate national output. If money is neutral, it means that money just affects prices. Economists and policy makers ought to use appropriate monetary policies for controlling macroeconomic volatilities. We suggest examining each country as individual, so that maybe other results will get, and also money can be neutral in some countries individually. Acknowledgment Hereby I would like to thank Dr. Ehsan Shafeie and Reza Mohammadpour for their useful help and comments. REFERENCES Abbasinejad, H., Shafeie, A. (2005). Is money neutral in Iranian economy?, Journal of Economic Research,Vol. 68, pp Blanchard, O.J., Quah, D. (1995), Misinterpreting the dynamic effects of aggregate demand and supply disturbances, Economics Letters, Vol. 49, No. 3, pp Bhargava, U., Bar-Lev, M., Bellows, C. G., Aubin, J. E. (1988). Ultrastructural analysis of bone nodules formed in vitro by isolated fetal rat calvaria cells. Bone, Vol. 9, No. 3, pp Bonato, Leo. (2007). Money and inflation in the Islamic Republic of Iran. International Monetary Fund. Bouoiyour, J., Selmi, R. (2014). GCC Countries and the Nexus between Exchange Rate and Oil Price: What wavelet decomposition reveals? International Journal of Computational Economics and Econometrics, Vol. 5, No. 1, pp Cover, James. P. (1992). Asymmetric Effects of Positive and Negative Money-Supply Shocks. Quarterly Journal of Economics, Vol. 107, pp Damette, O., Seghir, M. (2013). Energy as a driver of growth in oil exporting countries?, Energy Economics, Vol. 37, pp Entorf, H. (1997). Random Walks with Drift: Nonsense Regression and Spurious Fixed Effect Estimation. Journal of Econometrics, Vol. 80, pp Gujarati, D. N. (2004). Basic Econometrics, (4th edition). McGraw-Hill, New York. Harris, R. D., Tzavalis, E. (1999). Inference for unit roots in dynamic panels where the time dimension is fixed. Journal of econometrics, Vol. 91, No. 2, pp Im, K.S., Pesaran, M.H., Shin, Y. (2003). Testing for Unit Roots in Heterosgeneous Panels, Journal of Econometrics, Vol. 115, pp Kireyev. Alexei. (2000). Comparative macroeconomic dynamics in the Arab world: A panel VAR approach., IMF Working Paper WP/00/54, pp Lashkary, M., Kashani, B. H. (2011). The Impact of Monetary Variables on Economic Growth in Iran: A Monetarists Approach. World Applied Sciences Journal, Vol. 15, No. 3, pp Levin, A., Lin, C., Chu, Ch. (2002). Unit root tests in panel data: Asymptotic and finite-sample properties. Journal of Econometrics, Vol. 108, No. 1, pp Mandala, R., Takenobu, T., Hozumi. T. (1999). Combining multiple evidence from different types of thesaurus for query expansion. In Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval, pp Mehrara, M., Mohaghegh, M. (2011). Macroeconomic dynamics in the oil exporting countries: a panel VAR study. International Journal of Business and Social Science, Vol. 2, No. 21, pp Newbold, P., Granger, C. W. (1974). Experience with forecasting univariate time series and the combination of forecasts. Journal of the Royal Statistical Society, Series A (General), pp Pedroni, P. (2004). Panel cointegration: asymptotic and finite sample properties of pooled time series tests with an application to the PPP hypothesis. Econometric theory, Vol. 20, No. 03, pp Snowdon, B. V., Howard. R.- Wynarczyk., Pooran. A. (1994). A Modern Guide to Macroeconomics: An Introduction to Competing Schools of Thought, Aldershot: Edward Elgar World Bank. (2014). World Development Indicators. 6

7 7