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Oil and Dutch Disease

ECONOMICS FOR BUSINESS Project Report on – Oil and the recent ?Dutch Disease? – The Case of the United Arab Emirates Submitted by – Amitava Manna 1|Page Table of Contents Introduction ……………………………………………………………………………………………………………………………….. 2 Purpose ……………………………………………………………………………………………………………………………………… UAE Background ………………………………………………………………………………………………………………………….

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4 Theoretical Framework ………………………………………………………………………………………………………………… 4 Empirical Findings and Analysis …………………………………………………………………………………………………. 6 Data ……………………………………………………………………………………………………………………………………….. Descriptive Statistics ………………………………………………………………………………………………………………… 6 The Regression Model ……………………………………………………………………………………………………………… 8 Conclusions: ………………………………………………………………………………………………………………………….. 10 2|Page Introduction Four decades ago, the United Arab Emirates (U. A.

E) landscape and infrastructure consisted of not much more than deserts where sheikhdoms survived on fishing, pearling, herding and agriculture. Today, Abu Dhabi and Dubai are two of the most developed emirates in the country dominated by roads, luxury homes, and skylines (consisting of modern glass and steel skyscrapers). The new modern infrastructure has replaced the undeveloped cities that once existed before. To say the least U. A. E has transformed from a desert into a developed country1 with a high gross domestic product (GDP) reaching $192. 03 million2 in 2010. According to the Global Competitiveness Report 2008-2009, U. A. E was ranked number 31 globally for its growth competitiveness. The large boost in U. A. E? s development and economy is founded on the export of the country? s oil and petroleum-based products since 1958, when oil was first discovered in Abu Dhabi. Almost 10 percent (%) of the world? s current oil reserves are controlled by the U. A. E, enabling it to command more than 16% of OPEC? s total reserves. The aim of the U. A. E? economy is to minimize its dependency on oil; therefore much focus has been targeted on diversifying the economy during the past two decades. In turn, making it more dependent on the service sector, especially high-class tourism as well as expanding the international finance sector. In both developed and developing countries, a natural resource boom, (as experienced in U. A. E) has triggered the so called „Dutch Disease?. It is a theory that originates from the Netherlands in the 1970s, basically explaining a decline in the traditional manufacturing sector when the country experiences a boom in their natural resource.

The Dutch Disease indicates that the natural resource abundant factor triggers an appreciation of the domes- tic currency. In turn, other non-resource exporters are affected at the same time and the manufacturing sector experiences a constrained activity to compete in the world market. Furthermore, the agricultural sector undergoes a decline as labor moves to either the booming sector or the non-tradable sector. The case of the Dutch Disease would be a problem to the U. A. E since it causes the shift of labor and production for the tradable sector to the non-tradable sector causing a decline in the country? exports of manufacturing and agricultural goods. The decline in exports of U. A. E? s traditional tradable goods de-creases production of the goods affecting the country? s economy in a negative way. Purpose The purpose of this paper is to study U. A. E? s development in economic growth since 1975 and establish if there are any signs of the Dutch Disease by testing the ratio of tradable goods to non- tradable goods and the effects by other macroeconomic variables. 3|Page UAE Background U. A. E consists of the seven emirates Abu Dhabi, Dubai, Sharjah, Ra? al-Khaimah, Ajman, Umm al-Qaiwain and Fujairah, which are located on the southern Arabian Gulf. On the 2nd of December 1971, the country became independent after being under British rule for a period of 70 years. The independence and discovery of oil triggered the economic development in U. A. E which led to a huge expansion in the population. The population boom in U. A. E is a result of the increased demand for labor throughout the past four decades and consists for the most part (83%) of labor from foreign countries referred to as expatriates. United Nation? (UN) database illustrates the division of the labor from two perspectives; first from the year 2000 compared to the changes that prevailed in 2010. Female participation and male participation in 2000 consisted of 34. 4% in the former group and 92% in the latter group. As stated in the introduction, one of the impacts when an economy is experiencing signs of the Dutch Disease is the high inflation rate followed by a change in the real exchange rate. Fluctuations in the real exchange rate can cause resources and production to reallocate between the economy? sectors of tradable and non- tradable goods and services and is there-fore regarded as an important price in the economy. The U. A. E is one of the countries in the Middle East which follows a pegged (or fixed) ex- change rate regime, in which foreign central banks stand ready to buy and sell their currencies at a fixed price in terms of dollars. The currency of the U. A. E, the AED was first officially pegged against the USD in 1974. By the end of 1977 fluctuations occurred widely. For over two decades the USD had been used as an anchor currency in practice when it became the official anchor currency in 2002.

The decision to make the USD an anchor currency was made by the member nations of the Gulf Cooperation Council (GCC) in order to establish a common currency in 2010. The U. A. E and the effects from the oil industry have not been studied to any great extent. However some studies on the Dutch Disease concerning other countries have been conducted, but these studies are mainly theoretical and lack econometric testing. The studies with statistical analysis contain time series, more observations and flexible exchange rates (which could be included in the regression model). Theoretical Framework

In order to comprehend the Dutch Disease theory, theoretical model of tradable (T) and non- tradable goods4 (NT), also known as the TNT Model can be used. According to Sachs and Larrain (1993) the most important assumptions is that N can neither be exported nor imported and its domestic consumption and production must be equivalent. The opposite applies for T, consumption and production domestically can differ because of the possibility of imports and exports T. In this specific model, two goods are produced and 4|Page consumed: T and N by one factor of productivity which is labor.

The supply side obtains two linear functions: QT = aTLT (T) and QN = aNLN (N), Where, production is dependent on labor. LT and LN accounts for the amount of labor used, whilst aT and aN are the marginal productivities of labor for the two sectors. In other words a T or aN units more of output is achieved if one extra unit of labor is applied in either sector. Due to the linear functions, aT and aN also account for average productivities. The demand side of the TNT model circles around consumption decisions which do not include investment spending. Total absorption, i. e. pending on T and N is expressed in the equation as followed: A = PTCT + PNCN Total absorption is defined by A and levels of consumption for T and N by CT and CN. PT and PN correspond to the price of the goods. Furthermore, Sachs and Larrain (1993) assume if the ratio CT/CN is fixed, then households consumes CT and CN in fixed proportions, (regardless of relative prices). If overall spending increases, it is followed by an increase in consumption in T and N by the same proportion and vice versa. Figure below illustrates the production possibility frontier (PPF), the consumption line and the market equilibrium for T and N in a country.

The PPF shows each quantity of QT that is produced in order to produce the maximum quantity of QN. If QN = aNL then QT = 0, represented by point B in the figure. Then the factor of productivity labor is located in the N sector. If QN = 0 and QT = aTL, then labor is located in T (point D in the figure). The slope of the PPF is equal to PT/PN, i. e. the relative price of T in terms of N, which is also referred to as the real exchange rate, e, in the TNT model. Therefore, aN/aT = PT/PN = e. Figure: The PPF, Consumption Path and Equilibrium QNCN B G H ` F C E D A 5|Page QTCT

Empirical Findings and Analysis Data Summary of the Macroeconomic Variables used in the Regression Ratio of tradable goods to non- tradable goods (R) Sum of tradable goods (manufacturing value added, agriculture value added) divided by the sum of non-tradable goods (services value added). Inflation as GDP deflator in annual percent. Variables that are used to classify data into mutually special categories. Here the dummy variable represent the period 1975-1980, since the change in oil price was dramatic during these years. Based on current prices and is ex-pressed in USD per barrel

UN (2010) Inflation (I) Dummy variable (D1) Nation Masters Economy Statistics, U. A. E (historical data) (2010) Gujarati (2010) Price of oil (P) Annual Statistical bulletin OPEC (2010) Other variables were also tested, but due to insignificant values and to avoid problems of correlation, some of the variables were excluded from the regression models. One of the other variables tested was money supply (M1), but since this variable was highly correlated with GDP, we decided to exclude it. GDP was also excluded due to high correlation with the price of oil. Descriptive Statistics

The following figure shows the change in value added of tradable goods and non-tradable goods in U. A. E throughout the period 1975-2005 expressed in billion of AED per year. Value Added in Tradable and Non-tradable in U. A. E, 1975-2009 6|Page Value (BAED) 350 300 250 200 150 100 50 0 NT T As can be seen the production of non-tradable goods has been larger than tradable goods (non-oil goods) during the entire period. The tradable sector has not in-creased as much as the non- tradable sector, i. e. non-oil production has decreased in comparison to non-tradable.

In fact the non-tradable sector has increased almost twice as much as the tradable sector, which is a symptom of the Dutch Disease. One of the reasons why the non-tradable sector may have increased so much could be due to the country? s rise in export of oil throughout 1975-2009. US $ per Barrel 60 50 40 30 20 10 0 Price of Oil Inflation Rate Figure illustrates the relationship between the price of oil and the inflation rate during the period 1975-2005. We will concentrate on analyzing the inflation rate? s peak and lows and the impact from the fluctuating oil price.

We can first see that there was a sharp decline in inflation from 19758 until 1978. During 1974 the inflation rate was 138. 26% according to Nation Master Economy Statistics (2010). The sharp decline could be due to that the U. A. E officially pegged 7|Page the AED to the USD in 1974. The fluctuation in the inflation rate cannot only be explained by a boom in production but also depends on other factors as well, such as the depreciation of the USD. One of the reasons why the inflation in U. A. E change so dramatically during the years 1998-2001 could be due to the burst of the “I.

T-bubble” (known as the “Dot-com bubble”) in the late 1990s which affected USD negatively. The Regression Model In order to test if the chosen macroeconomic variables show indications of symptoms of the Dutch Disease, the model with the ratio of tradable goods to non-tradable goods was adopted but adjusted in order to fit this thesis. The adjusted equation is based on time series data. The presented macroeconomic variables; inflation (I) is based on the theoretical framework presented, price of oil (P) is adopted which included price of oil in the regression analysis.

The dummy variable (D1) for the period 1975-1980 is which included a dummy variable for a one year period. The ratio of tradable goods to non-tradable goods serves as the dependent variable in both models, however the independent variables differ slightly; the first regression model includes inflation and price of oil as the independent variables. The second regression model also includes inflation and price of oil but a dummy variable for the period 1975-1980 was added. Model 1: R = ? 0 + ? 1P + ? 2I + ? Model 2: R = ? 0 + ? 1P + ? 2I + ? 3D1 + ? 4. 4. Econometric Problems In the beginning of the regression testing we discovered that some of the variables were correlated with one another. Money supply (M1) and GDP were the most correlated variables in the regression models, so in order to avoid multi co linearity problems we decided to exclude money supply and GDP from the regression model. The reason why the two variables were excluded was due to the high correlation between GDP and money supply and the high correlation between GDP and price of oil. Coefficient ?1 (Price of Oil) ?2 (Inflation) ?3 (Dummy Variable) . 5 Regression Results: Sign negative or no effect negative negative or no effect 8|Page In order to make it more comprehensive for the reader, the authors summarized the coefficients and significance levels (1%, 5% or 10%) from the two different regression model results with 36 observations for the period 1975 to 2010. The R-square values show that 39. 3% (model 1) and 75. 3% (model 2) of the change in the ratio of tradable goods to non-tradable goods can be explained by the model used. The goodness of fit in model 1 on the other hand, has a poorer fit, where 39. % of the influences on the dependent variable can be explained by the model. The better fit of model 2 can be due to the additional variable tested in the second regression model, i. e. D1. In model 1 and 2 the price of oil is significant and does not support the expectation that it would have a negative or no effect on the ratio. Price of oil is significant at a 1% significance level in model 1 and affects the dependent variable positively. A 1% increase in the ratio of tradable goods to non-tradable goods would increase the price of oil by 0. 05840%, all else equal. In the second regression model, the price of oil is significant at a 1% level, meaning that a 1% change in the regress and would increase the price of oil by 0. 002988%, all else equal. The results from the regression models indicate that the price of oil has a positive effect on the dependent variable. This result corresponds to the authors? expectations that during a boom in natural resources, inflation has a negative effect on the ratio. The negative relationship between the inflation rate and the ratio can also be xplained by the spending effect since in a fixed exchange rate regime the inflation rate is affected by the in-crease in the money supply. The second hypothesis for model one is therefore not rejected and the authors can conclude that the macroeconomic variable inflation is a symptom of the disease in the country. However in the second model the inflation variable is not significant and the authors can thereby not take the variable into consideration when analyzing if the U. A. E experienced the Dutch Disease during the years 1975- 1980.

Furthermore, the insignificant value of the inflation rate in model two might be due to the short time period tested, 1975-1980. The major oil price shock during this period had a negative impact on the economy of U. A. E, which negatively affected the inflation rate, leading to the insignificant-cant value in the second regression model. Time Series Regression Model 1 & 2: Model 1: R = ? 0 + ? 1P+ ? 2I + ? Coefficient Variable (t-stat) Constant 0. 166071*** (5. 141492) Price of Oil (P) 0. 005840*** (4. 122855) Inflation (I) -0. 352179* (-1. 38647) R2 = 0. 393393 DW = 0. 238252 *** Significant at 1% level ** Significant at 5% level * Significant at 10% level Model 2: R = ? 0 + ? 1P+ ? 2I + ?3D1 + ? Coefficient (t-stat) Constant Price of Oil (P) Inflation (I) Dummy Variable (D1) R2 = 0. 753809 DW = 0. 416614 0. 242127*** (10. 00689) 0. 002988*** (2. 915261) -0. 016530 (-0. 127760) – 0. 144894*** (-6. 287065) 9|Page Conclusions: This project is a study whether the oil boom in U. A. E during the 1970s led to symptoms of the Dutch Disease and if the country is a victim of the disease.

Three hypotheses were tested and descriptive data was analyzed in order to reach a conclusion. The first hypothesis tested the authors? statement that the price of oil has a negative (or no) effect on the ratio of tradable goods to non-tradable goods. The results showed that the price of oil did have a positive effect on the ratio, meaning that even though there are changes in the price of the natural resource it does not affect the production in the non-oil sectors to decline. Hypothesis 1 is therefore rejected by us.

In the mid-1980s the disease took an opposite direction when oil prices collapsed. Domestic demand dropped sharply in the oil-rich countries causing the construction industry to experience unemployment and employment shifted back to the tradable goods sectors. Therefore it can be concluded that the price of oil cannot be considered as a symptom of the Dutch Disease in the U. A. E. The second hypothesis was based on the problems of the high inflation rate U. A. E has experienced on and off during the years.

Inflation was stated to have a negative effect on the ratio of tradable goods to non-tradable goods due to the fixed exchange rate. The regression results showed that inflation held a negative impact on the ratio therefore the hypo-thesis is not rejected by us. The last hypothesis was based on the high oil prices that existed during the period 1975-1980. Therefore a dummy variable was included in the hypothesis with the statement that it would have a negative (or no) effect on the ratio of tradable goods to non-tradable goods.

Results showed that the dummy variable was negatively correlated with the ratio, thus the third hypothesis is not rejected. The negative relationship is in line with our expectations. One explanation for the negative impact on the ratio could be due to the oil price shock that occurred in 1979. The increase in the oil price during these years therefore affected the oil production negatively. Furthermore, the price of oil can be seen as a possible symptom of the Dutch Disease in U. A. E? s economy.