IMPACT OF EXCHANGE RATE ON TRADING BALANCE

JUMA YAZIDI

A DISSERTATION SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE IN ECONOMICS OF THE OPEN UNIVERSITY OF TANZANIA

2013

CERTIFICATION

The undersigned certify he has read and hereby recommend for acceptance by the Open University of Tanzania a dissertation entitled: “Impact of Exchange Rate on Trade Balance” in partial fulfillment of requirements for Master of Science in Economics

………………………………...

Dr. Khatibu Kazungu

(Supervisor)

Date………………………………..

DECLARATION

I Juma Yazidi, declare that this dissertation is my own original work and that it has not been presented and will not be presented to any other University for a similar degree award.

Signature ……………………………………

Date………………………………..

COPYRIGHT

No part of this dissertation may be reproduced, stored in any retrieval system, or transmitted in any form by any means, electronic, mechanical, photocopying, recording or otherwise without prior written permission of the author or the Open University of Tanzania in that behalf.

DEDICATION

I dedicate this work to my parents, the late father Juma Nshaija and my mother Hafsa Abdallah for their parental care and sacrifice towards my education carrier development. May Allah rest the soul of late father in everlasting peace and give my mum a health and long loving life. Amin

ACKNOWLEDGEMENT

I would like to extend my sincere thanks to all those whose viable contributions made me get encouragement and later realize a success in writing this dissertation. Many thanks are to Dr Khatibu Kazungu of the Open University of Tanzania who provided me with all the guidance in writing this dissertation.

With genuine humility and great respect I wish to thank my lecturers Dr Felician Mutasa, Dr Deus Ngaruko of The Open University of Tanzania, Dr Jehovaness Aikael, Dr Razack Lokina, Dr Vicent Leyaro of University of Dar es salaam for their tireless efforts to provide me Economics education during my study as Msc.Economics Student. I wish to thank my Uncle Saad Kajuna, My friend Mr Burchard Rwamtoga for their encouragement all the time.

I deeply appreciate the effort made by my colleagues students Elinaza Abdul, Josephat Mshumbusi ,James Mbongo, Francis Assenga, Mathew M. who from time to time kept on inspiring me to continue relentlessly in conducting and writing this dissertation.

Lastly but not least I wish to thank my family for their tolerance when I was far away from them for sake of this study. I also thank all those might have helped me in one way or another in the completion of this study but unfortunately their names do not appear here. I still appreciate their contribution. None of the mentioned people however, are to blame for any shortcomings that study may contain; I am solely responsible for them.

ABSTRACT

This study examines the relationship between exchange rate changes and trade balances in Tanzania for the period 1970 to 2010. The null hypothesis is that there is no relationship between the exchange rate and trade balances. To avoid spurious regression problems, the data were tested for stationarity and Cointegration. Augmented Dick -Fuller (ADF) tests show that the series were non stationary at Level but all of them are stationary at their first difference. The Engle granger Cointegration Test shows that there is a long run relationship between Trade balance, Exchange rate, Tanzania’s GDP and World income. Our findings are as follows Exchange rate; World income and Tanzania’s GDP have positive relationship with Trade balance. This means that Tanzania can depreciate Exchange rate to improve its Trade balance.

TABLE OF CONTENTS

CERTIFICATION	ii

DECLARATION	iii

COPYRIGHT	iv

DEDICATION	v

ACKNOWLEDGEMENT	vi

ABSTRACT	vii

TABLE OF CONTENTS	viii

LIST OF TABLES	xii

LIST OF FIGURES	xiii

ABBREVIATIONS	xiv

CHAPTER ONE	1

1.0 INTRODUCTION	1

1.1	Background to the Study	1

1.2	Statement of the Problem	1

1.3	General Objective of the Study	2

1.3.1 The specific Objective of the Study	3

1.4	Hypothesis	3

1.5	Significance of the Study	4

1.6	Scope of the Study	5

1.7	Organization of the Study	5

CHAPTER TWO	6

2.0 OVERVIEW OF EXCHANGE RATE ON TRADE BALANCE	6

2.1 Introduction	6

2.2 Trade Balances and Economic Performances in the Period 1970-1980	6

2.4 Trade Balance and Economic Performance in the Period 1991-2000	16

2.5 Trade balance and Economic Performance in the Period 2001-2010	18

2.6 Summary	20

CHAPTER THREE	22

3.0 LITERATURE REVIEW	22

3.1 Introduction	22

3.2 Theoretical Literature Review	22

3.2.1 J-curve	23

3.2.2 The Elasticity Approach	24

3.2.3 Mundell – Fleming Model	25

3.3 Empirical Literature Review	25

3.4 Summary	40

CHAPTER FOUR	41

4.0 RESEARCH METHODOLOGY	41

4.1 Introduction	41

4.2 Measurement of Variables	41

4.2.1 Real Exchange Rate Measurement	41

4.2.2 Measurement of Trade Balance	42

4.2.3 Measurement of Other Variables	42

4.3 Model Specification	42

4.4 Data Sources	44

4.5 Estimation Techniques	44

4.5.1 Stationarity Test	44

4.5.2 Cointegration Test	45

4.6 Summary	46

CHAPTER FIVE	47

5.0 ECONOMETRIC ANALYSES	47

5.1 Introduction	47

5.2 Analyses Descriptive Statistics	47

5.3 Stationarity Tests (Unit Root Test)	47

5.4 Cointegration Test and Error Correction Model	49

5.4.1 Cointegration Analyses	49

5.4.2 Error Correction Mechanism	50

5.4.3 Diagnostic Test	51

5.4.4 Interpretation of Results	52

5.5 Comparison with Other Studies	53

5.6 Summary	55

CHAPTER SIX	56

6.0 CONCLUSION AND RECOMMENDATION	56

6.1 Introduction	56

6.2 Summary of the Study	56

6.3 Findings of the Study	56

6.3 Policy Implications	57

6.4 Limitations of the Study	58

6.5 Area for Further Studies	58

REFERENCES	59

APPENDICES	69

LIST OF TABLES

Table 1.0: Export to Import ratio	2

Table 2.1: Trade Balance and Exchange Rate for Period 1970 to 1980	6

Table 2.2: Trade balance and exchange rate for the period 1981 to 1990	10

Table 2.3: Trade Balance and Exchange Rate for the Period 1991 to 2000	16

Table 2.4: Trade balance and exchange rate for the period 2001 to 2010	18

Table 5.1 Summary of the Descriptive Statistics of the Data	48

Table 5.2: Unit Root Test Results	49

Table 5.3: Cointegration Test for Residual Estimation	50

Table 5.4: Error Correction Model Results for Trade Balance The Dependent Variable	51

LIST OF FIGURES

Figure 2.1: Graph of Import and Export for the Period 1970 to 1980	7

Figure 2.2: Bargraph of Import and Export for the Period 1970 to 1979	7

Figure 2.3: Showing Exchange Rate for the Period 1970 to 1980	8

Figure 2.4: Import and Export for the period 1981 to 1990	10

Figure 2.5: Bar-graph of Export and Import for the Period 1981 to 1990	11

Figure 2.6: Exchange Rates for the Period 1981 to 1990	11

Figure 2.7: Bargragrah of Export and Import for the period 1991 to 2000	17

Figure 2.8: Bargraph of Export and Import for the Period 2001 to 2010	18

Figure 2.9: Exchange rate for the period 2001 to 2010	19

Figure 2.10: Trade balance for the period 1970 to 2010	20

Figure 2.11: Exchange rate for the period 1970 to 2010	20

ABBREVIATIONS

ADF	:	Augumented Dick Fuller

AIC :	Akaike Information Criterion

BG :	Breusch-Godfrey

BOT :	Bank of Tanzania

CPI :	Consumer price index

ECM :	Error Correction Mechanism

EG :	Engle-Grangler

IMF :	International Monetary Fund

OLS :	Ordinary least square

RER :	Real Exchange Rate

TB :	Trade Balance

TGDP :	Tanzania’s Gross Domestic Product

UK :	United Kingdom

USA :	United States of America

WGDP :	World Gross Domestic Product

WPI :	Whole Price Index

CHAPTER ONE

1.0 INTRODUCTION

Background to the Study

The exchange rate affects exports through its effects on competitiveness. The appreciation of the exchange rate implies that the cost of producing tradable goods is increasing and hence the country losses the competitive in the international market (Waane, 2000). It raises the demand for imports and reduces demand for exports. Therefore in order to promote export it is advisable to stabilize exchange rate such that there are small fluctuations in the exchange rate.

The trading activities of Tanzania and other countries in the period 1970 to 2010 were not impressive as indicated by the export to import ratio of less than unity as shown in Table 1. This suggests that Tanzania suffered a negative trade balance for more than forty years although its exchange rate has been depreciating. May be there are other factors affecting the trade balance such as World income and Domestic income. This has attracted me to study how exchange rate and those factors have affected trade balance and its contribution to the economy of the country through trade balance.

Statement of the Problem

Tanzania has implemented economic reforms since the late 1980s, including depreciating its exchange rate in order to improve its trade balance, however instead of progressively improve its trade balance the export to import ratio remained less than unity and the trade balance has worsened. Specifically, between 1985 and 2010 exchange rate was falling in value but trade deficit remained to be less than unity. In this study we examine effects of the exchange rate and other variables on trade balance.

Table 1.0: Export to Import ratio

Year	TB	Year	TB	Year	TB
1970	0.79	1984	0.47	1998	0.41
1971	0.71	1985	0.28	1999	0.35
1972	0.80	1986	0.37	2000	0.44
1973	0.74	1987	0.31	2001	0.45
1974	0.53	1988	0.33	2002	0.54
1975	0.48	1989	0.35	2003	0.53
1976	0.68	1990	0.24	2004	0.51
1977	0.68	1991	0.22	2005	0.51
1978	0.68	1992	0.26	2006	0.41
1979	0.42	1993	0.29	2007	0.42
1980	0.45	1994	0.35	2008	0.42
1981	0.41	1995	0.40	2009	0.46
1982	0.48	1996	0.51	2010	0.49
1983	0.38	1997	0.56

Source of Data: Bank of Tanzania (BOT Repot, 1980, 1990, 2010)

The table 1.0 above shows the ratio of export to import, which is less than one since 1970 to 2010

General Objective of the Study

The general objective of the study is to examine the impact of exchange rate on trade balances.

1.3.1 The specific Objective of the Study

The specific objective of the study

To examine a relationship between exchange rate changes and trade balance.

To examine a relationship between Domestic income and Trade Balance.

To examine a relationship between world income and Trade Balance.

Hypothesis

The hypothesis of this study will be

(i) Null hypothesis, Ho: B1= 0

No significant relationship between Exchange rate changes and trade balance in Tanzania in the period 1970 to 2010.

Alternative hypothesis, H1: B1 0

There is significant relationship between Exchange rate and Trade balance in Tanzania in the period 1970 to 2010.

(ii) Null hypothesis, Ho: B2 = 0

No significant relationship between domestic income and trade balance in Tanzania in the period 1970 to 2010.

Alternative hypothesis, H1: B20

There is a significant relationship between domestic income and trade balance in Tanzania in the period 1970 to 2010.

(iii) Null hypothesis, H0: B3 = 0

No significant relationship between world income and Trade balance in Tanzania in the period 1970 to 2010.

Alternative hypotheses, H1: B3 0

There is significant relationship between World income and Trade balance in Tanzania for the period 1970 to 2010.

Significance of the Study

Quantifying the short-run and long-run responsivess of the merchandise trade balance to exchange rate changes is important to economic policy for several reasons. First, it establishes whether there is a stable long-run relationship between the exchange rate and the merchandize trade balance. If such a stable long-run relationship does not exist, then depreciating the exchange rate does not seem to be a reasonable solution for improving the country’s competitiveness on the long-term basis. Other factors such as domestic income, World income should be investigated for this purpose.

Second if a long-run relationship does exist, then it is necessary to establish whether it is likely that depreciation leads to a net improvement of the trade balance in the long-run. Third, quantifying the extent of the trade balance improvement would be desirable to weigh the trade balance benefits against costs of permanent depreciation. Fourth, the estimate of the short-run dynamics provides information regarding the immediate and medium impact of exchange rate changes on the balance. More specifically, the question here is whether depreciation has an adverse short run impact on the merchandize trade balance. If it does, it seems reasonable to estimate the persistence and extent of the adverse effect. This is empirical question and in the literature it is known as the J-curve effect. Fifth, the results presented may contribute to further insights in the international transmission of changes in the economic activity and prices.

Sixth, in broader sense information regarding the impact of expenditure reducing policies, monetary and fiscal on domestic trade balance. Seventh, it might encourage further analysis with respect to the impact of substantial government foreign lending on trade balance and current account in general. Eight, the result might eventually play a role in evaluating appropriateness of an asymmetrical central bank intervention policy with respect to an alternative such as the introduction of crawling peg exchange rate policy in order to support a permanent depreciation of the domestic currency (Stucka, 2004).

Scope of the Study

This study will only be limited to Tanzania, taking exchange rate and GDPs for Tanzania since 1970-2010 to represent domestic income and GDPs for UK, USA, Japan, India, Spain, China and France to represent World income.

Organization of the Study

The rest of this study is organized as follows: Chapter two gives overview of the impact of exchange rate on the trade balance in Tanzania since 1970 -2010, also discusses the economic developments in that period. Chapter three reviews the relevant literatures and provides major gaps in earlier work that are addressed by the present study. Chapter four describes the hypothesis and methodology that used in this study. Chapter five presents and discusses empirical results from this study. Finally, chapter six provides concluding remarks, policy implications and offers recommendations based on empirical findings of this study. It also suggests areas for further study.

CHAPTER TWO

2.0 OVERVIEW OF EXCHANGE RATE ON TRADE BALANCE

2.1 Introduction

This chapter provides the background to the performance of the Tanzania Economy and also discusses Tanzania’s Trade balance developments from 1970 to 2010. In some special cases we explained how exchange rate affected Trade balance or failed to have effect on trade balance. The period from 1970 to 2010 is divided into four sections.

2.2 Trade Balances and Economic Performances in the Period 1970-1980

In this period Tanzania suffered a severe trade deficit as the trade balance widened or the Export to import ratio decreased as shown in the Table 2.1 and figure 2.1 below. However the exchange rate in the year 1970 to 1972 was not changed, then we can say that the authorities concerned did not take measures to improve the trade balance through exchange rate. In the next two years (1973 to 1974) Tanzania’s exchange rate appreciated which affected trade balance negatively (BOT, 1976).

Table 2.1: Trade Balance and Exchange Rate for Period 1970 to 1980

Year	EXPORT/IMPORT (TB)	Tzs/ US EXCHANGE RATE
1970	0.790325418	7.14
1971	0.701797506	7.14
1972	0.802185224	7.14
1973	0.741908594	7.02
1974	0.535261298	7.13
1975	0.484063047	7.37
1976	0.68846729	8.38
1977	0.681334199	8.29
1978	0.417037963	7.71
1979	0.451427312	8.22
1980	0.406625922	8.20

Source of Data: Bank of Tanzania

0 2000 4000 6000 8000 10000 12000 70 71 72 73 74 75 76 77 78 79 80 EXPORT IMPORT Figure 2.1: Graph of Import and Export for the Period 1970 to 1980

Figure 2.2: Bargraph of Import and Export for the Period 1970 to 1979

Figure 2.3: Showing Exchange Rate for the Period 1970 to 1980

The depreciation of exchange rate in this period (i.e between 1970 and 1980) could have improved the trade balance but on contrary to the expected results, the balance of trade (BOT) worsened (see figure 2.2). But in some years there was an improvement for example in the year 1976 the trade balance deficit showed considerable improvement over the previous year (1975) declining from Shs 2,940 million in 1975 to 1,242 million. This marked improvement is attributed to strong rise in export receipts coupled with a slight fall in imports. Total exports grew by as much as 47.3%, in sharp contrast to the decline of 3.4% in 1975.The large improvement of exports was partly due to favorable prices for some of Tanzania’s major export commodities, notably coffee, cotton, and tobacco and partly due to the large volume exported following a significant rise in production. However, the performance of other main commodities-sisal, cashewnuts and cloves, was rather, disappointing (BOT, 1975).

Export of manufactured products as a group registered an increase of 30.6% over the preceding year. In 1976 total imports showed a small decline of 6.6%.The main factors behind the decline were (i) Increased domestic food production which considerably reduced the need for large imports of food grains (ii) the completion of major development projects eg. TAZARA and Kidatu phase I and (iii) the continued events of imports control measures that had been taken in the previous two years following the sharp deterioration in the country’s balance of payments position (BOT, 1976).

During the year 1978 Trade balance deteriorated, the marked deterioration is significantly attributed to decline in export earnings coupled with large rise in export bill. Export earnings fell from Shs 4,518.5 million in 1977 to Shs 3,634.8 million representing a decrease of 19.6% while import rose by as much as Shs 2,667.4 million or 43% to 8,866.9 million (BOT, 1978).

2.3 Trade Balance and Economic Performance in Period 1981- 1990

In this period, Tanzania continued to suffer from trade deficit as shown by the table 2.2 below. We can say on average the trade balance worsened though the effort made to depreciate the exchange rate to improve the trade balance did not help. In some years we have provided the reasons for the fluctuations. We did this for year 1981, 1982, 1986,1987,1988,1989 and 1990. FIGURE 2.4 and 2.5 shows that imports have been exceeding exports in the entire period, while exchange was depreciating. (Figure 2.6)

Table 2.2: Trade balance and exchange rate for the period 1981 to 1990

Year	Balance Of Trade	Exchange Rate
1981	0.483191293	8.28
1982	0.394675683	9.28
1983	0.466114678	11.14
1984	0.454573708	15.29
1985	0.285112641	17.47
1986	0.369068254	32.70
1987	0.311964948	64.26
1988	0.334549908	99.29
1989	0.350792407	143.38
1990	0.242762723	195.06

Source: Bank of Tanzania (1990)

Figure 2.4: Import and Export for the period 1981 to 1990

Source: Bank of Tanzania (1990)

Figure 2.5: Bar-graph of Export and Import for the Period 1981 to 1990

Source: Bank of Tanzania (1990)

0 40 80 120 160 200 81 82 83 84 85 86 87 88 89 90 EXCHANGE RATE Figure 2.6: Exchange Rates for the Period 1981 to 1990

Source: Bank of Tanzania (1990)

In 1981the performance of export sector was somewhat mixed. The modest improvement in agricultural exports during that year was almost entirely offset by the unsatisfactory performance of the industrial sector. Agricultural crops contributed shs3, 280.4 million or 67.6 percent the total export earnings in 1981 as against shs. 2,768.7 million or 58 percent of the total export in 1980. The increase of shs.511.7 million in agricultural exports was, however, offset to the extent of shs.482.5million by the fall in industrial exports. The increase in agricultural exports during 1981 vis-à-vis such in exports in 1980 resulted mainly from volume increases. Exports of coffee, cotton, sisal, raw cashew nuts and tobacco increased by 40.9 percent, 40 percent, 177.7 percent and 27.3 percent respectively and this increase, to a great extent, resulted from higher production of these crops.

The exports of manufactured goods and petroleum products declined steeply during 1981.The fall in exports of manufactured products was by 37.5 percent from shs.743.3 million in 1980 to shs.464.7 million in 1981. The export of petroleum products also dropped by 36.5 percent from shs.204.2 million in 1980 to shs.129.6million in 1981.

Total imports fell by 6.8 percent or by shs.692.8 million from shs.10, 260.6 million in 1980 to shs.9,567.8 million in 1981.This decline in imports was entirely accounted by the reduction in import volumes. Imports of capital goods rose during 1981 by 9.2 percent with machinery and transport equipment accounting for the increase. The imports of intermediate and consumer goods, however declined by 15.8 percent and 21.4 percent respectively.

The reduction in the trade balance deficit witnessed during 1981 continued during the first half of 1982.The trade balance deficit of Shs 1,359.6 million during this period was much lower than deficit of Shs 2,673.0 million registered during the first six months of 1981.This position emerged mainly as a result of the sharp drop in imports. Exports during the first half of 1982 were no doubt lower by 27.5% but the imports also dropped by a larger percent of 38.8 from the levels registered during the first six months of 1981 (BOT, 1981).

The calendar year 1986 saw Tanzania’s foreign trade deficit worsening from shs.12,449.1 million in 1985 to 22,935.5 million. Trade deficit worsened despite a more than two-fold increase in the shilling value of exports; from shs.5006.9 million in 1985 to shs.11, 391.1million in 1986.Most of the increase was accounted for by the depreciation of the domestic currency. In dollar terms, export earnings went up by 21.7 percent, from US$ 285.6 million in 1985 to US$347.6 million during 1986.The improvement in dollar value of export during that year was largely on account of buoyant coffee prices though export volumes of coffee and cotton also increased.

As a proportion of nominal GDP, export earnings rose from 5.0percent in 1985 to 8.7 percent during that year. In nominal terms, the shilling value of Tanzania’s imports went up by 96.6 percent or by 4.8 percent in US $ dollar terms. In real terms, however, imports dropped by about 0.2 percent as average unit prices are estimated to have risen by 5 percent. As was the case in the previous two years, the increase in imports was partly accounted for the increase in own-funded imports following liberalization of trade policy. As a ratio of nominal GDP, imports were 26.1 percent in 1986 compare to 17.6percent in 1985 (BOT, 1986).

During the calendar year 1987 the country’s foreign trade deficit widened despite the near doubling in the shilling value of exports, from Shs 10,981.8 million in 1986 to Shs 18,498.5 million in 1987.The increase in exports was largely an account of depreciation of the domestic currency. In terms of dollars, export earnings in fact went down by 3.6% from $366.3 million in 1986 to $353.2 million in 1987.However, as a proportion of nominal GDP, export earnings increased from 6.8% in 1986 to 8.1% in 1987.The shilling value of imports increased by more than twofold; from Shs 34,326.4 million in 1986 to Shs 73,899.0 million in 1987.Again the depreciation of the shilling largely accounted for the increase in imports. In US dollar terms imports went up by 9.8%.As a proportion of nominal GDP imports reached 32.4% in 1987 compared to 21.2% in 1986 (BOT, 1987).

During calendar year 1988, the country’s foreign trade deficit widened in both local currency and US dollar terms. In local currency the trade account registered a deficit of Shs 79,517.0 million compared with Shs 55,400.5 million a year earlier. The deficit widened despite a more twofold increase in the shilling value of exports resulting mainly from devaluation of the currency and despite a lower rate of growth in import bill. This is basically because of the underline fact that the volume of exports is only about a third of the volume of imports. In US dollar terms, the merchandise trade deficit widened by some 2 percent to reach US $812.18 million in 1988.Exports rose by 7.6% to US $380.20 million from US $353.2 million the year before, while imports increased by 3.7% (BOT, 1988).

30 June 1989 was the end of the three year Economic programme (ERR) whose implementation commenced in July 1986.The steady improvement which showed up in the real sector of the economy during the first two years of the programme was maintained during the year 1988/89.GDP at constant 1976 prices increased by 4.1percent the highest rate ever attained since 1980. This economic growth rate was above the 2.8 percent population growth rate as per 1988 population census, thus implying an improvement in the per capita income (BOT, 1989).

During the third quarter of 1990 the country’s foreign trade showed a deficit of Shs 77,591.42 million, much higher than the deficit of Shs 30,236 million registered in the corresponding quarter of the year before. The sharp widening of the deficit in Shilling terms was mainly on account of both the depreciation of the Tanzanian Shilling against foreign currencies and increased imports. In US dollar terms trade balance deteriorated during the period under review from a deficit of US $207.8 million recorded in the corresponding quarter of 1989 to a deficit of US $381.3 million.

The widening of trade deficit was due to a large import bill as well as depreciation of the domestic currency against foreign currencies. The increase in exports during January –September 1990, in local currency terms was mainly due to non-traditional exports with miscellaneous exports and manufactured goods on the lead. The trade account during that year deteriorated substantially because of poor export performance coupled with an increase in imports when compared with the levels recorded during the previous year. The trade account worsened to a deficit of USD 844.9 million as against deficit of USD 644.0 million recorded during 1987/88 (BOT, 1990).

2.4 Trade Balance and Economic Performance in the Period 1991-2000

In this period there was improvement in trade balance, especially from 1991-1995 but next four years (1996-1999) the trade balance deteriorated. While in the year 2000 there was little improvement. We have provided reasons for the fluctuations for some years.

Table 2.3: Trade Balance and Exchange Rate for the Period 1991 to 2000

Year	Trade Balance	Exchange Rate
1991	0.220384082	219.16
1992	0.275798701	297.71
1993	0.294074579	405.27
1994	0.346293929	509.63
1995	0.402904295	574.76
1996	0.565897964	579.98
1997	0.561313443	612.12
1998	0.405142284	664.70
1999	0.354785513	744.80
2000	0.43551477	800.40

Source: Bank of Tanzania

The deficit in the trade account increased by 7.5% in dollar terms from US $ 1036.7 million in 1990 to US $ 1114.5 million in 1991.The fall in both volume and price of some of the exports, as well as increased imports, contributed to the increase in deficit. (BOT report, 1991) The deficit on the trade account was narrowed to USD 1089.4 million, compared to a deficit of USD 1112.2 million reported in 1991.Although, there was also an increase in imports, the rise in exports was high enough to surpass the increase in imports and, hence reduce trade deficit. An increase in service earnings of USD 5.2 million in 1992 over the earnings of 1991, coupled with a decrease in service payments of 13.0 percent, explain a reduction of the deficit on the services account by 28.3% from USD 160.9 million in 1991 to USD 115.3 million in 1992 (BOT, 1992).

By 1994, the trade balance deficit deteriorated to US$ 644 million which was followed by the overall deficit in the balance of payment of about Tsh.76,614 million. This trend continued and trade account deficit decreased to about US$546 millon recorded during the same period a year before. (BOT annual report for 1991,1992 and 1994) In belief, we can say that the trade balance had little improvement in this decade, but still yet exports were greater than imports as shown the table below (Figure 2.7) .

Figure 2.7: Bargragrah of Export and Import for the period 1991 to 2000

Source: Bank of Tanzania (1990)

2.5 Trade balance and Economic Performance in the Period 2001-2010

In this period exchange rate depreciated continuously year after year (FIGURE 2.8) but still yet imports were greater than exports (Figure 2.9). We have again given reasons for the situations for some years. The whole decade Tanzania suffered trade deficit as shown by Tables 2.4.

Table 2.4: Trade balance and exchange rate for the period 2001 to 2010

Year	Trade Balance	Exchange Rate
2001	0.452792789	876.40
2002	0.544452475	966.60
2003	0.531516654	1,038.90
2004	0.538987328	1,089.10
2005	0.509049677	1,129.20
2006	0.408032868	1,253.90
2007	0.416657537	1,244.10
2008	0.415308529	1,196.30
2009	0.455980525	1,319.90
2010	0.4905522	1,432.30

Source: Bank of Tanzania

Figure 2.8: Bargraph of Export and Import for the Period 2001 to 2010

Source: Bank of Tanzania (1990)

Figure 2.9: Exchange rate for the period 2001 to 2010

Source: Bank of Tanzania (1990)

During 2006, Tanzania continued to record good overall macroeconomic reforms over the last decade. The economy was growing at average rate of 6.3 percent in in the past five years to 2006.However the growth rate of GDP in 2006 was 6.2 percent slightly lower than the 5 years average. The slow down economic activity in 2006 was on account of persistent drought which adversely affected agricultural product (BOT, 2006).

During the year ending June 2010 the value of goods export increased by 14.9 percent to USD 3754.2 million from the level recorded June 2009.largely due to an increase in export value of non- traditional commodities particularly gold, fish and fish products. The value of gold exports went up due to both price and volume factors. The value of goods import increased to USD 6570.3 million in that year ending June 2010 compared to USD 6220.5million recorded during the year ending June 2009, largely due to a rise in imports value of oil, industrial raw materials, food and other consumer goods.(BOT, 2010).

2.6 Summary

In summary we can say that Tanzania suffered Trade deficit since 1970 to 2010 as shown by Figure 2.10 below. On other hand exchange rate depreciated for the most of the period Figure 2.11 which implies that exchange rate depreciation did not help to improve the trade balance.

Figure 2.10: Trade balance for the period 1970 to 2010

Source: Bank of Tanzania (1990)

Figure 2.10 shows the Export to import ratios are less than unity since 1970 to 2010.

Figure 2.11: Exchange rate for the period 1970 to 2010

Source: Bank of Tanzania (1990)

Figure 2.11 shows the exchange rate of Tanzania since 1970 to 2010. From 1980 to 2010 the currency of Tanzania has been losing its value continuously.

CHAPTER THREE

3.0 LITERATURE REVIEW

3.1 Introduction

This chapter reviews the literatures which are in relation to this study. It starts by explaining theories pertaining this study, and then empirical studies already done, it then shows how the theories have been supported by empirical studies done and lastly it gives the summary of the reviews presented.

3.2 Theoretical Literature Review

Trade balance is the difference between value of exports and the value imports (Colander, 2004). It shows how a country is favored by trading in relation to other countries. A Country has a trade deficit if imports more than it exports; the opposite scenario is a trade surplus. Whereby Exchange rate can be defined as the cost of a currency in relation to other currencies of other countries (Colander, 2004). The changes in the exchange rate can change the relative price of imports and exports. For instance if the exchange rate is to appreciate (increase in value) then the price of exports will increase compared to their previous position, so causing a contraction in demand. In contrast the price of imports would appear to be relatively cheaper; this will cause extension in demand. The overall effect would be that the trade balance (exports minus imports) would deteriorate. In brief we can say that appreciation of exchange rate causes deterioration in the trade balance whereby depreciation of exchange rate causes improvement in the trade balance. There are several theories used to explain the impact of exchange rate changes in relation to Trade balances here we explain few of them.

3.2.1 J-curve

J-curve effect describes that in the short-run export volumes and import volumes do not change much so that the country receives less export revenue and spends more on imports leading to deterioration in the current account balance (Solderstein, 1995). However, after a time lag, export volumes start to increase and import volume starts to decline, this leads to the improvement in the trade balance.

“Most economists and policy makers believe that currency devaluations bring about competitive advantage in International trade, when a country devalues its currency, domestic export goods become cheaper relative to its trading partners resulting in an increase in quantity demand. Devaluation as a policy prescription is mainly aimed at improving the Trade balance. However there is a time lag before the trade balance improves following a real depreciation. The short and long run effects of depreciation on the trade balance are different. Theoretically, the trade balance deteriorates initially after depreciation and sometime along the way it starts to improve until it reaches its long-run equilibrium. The time path through which the trade balance follows generates a J-curve. The time lag comes about as an impact of several lags such as recognition, decision, delivery, replacement, and production (Junz and Rhomberg, 1973).

One explanation for the J-curve phenomenon is that the prices of import rise soon after real depreciation but quantities take time to adjust downward because current imports and exports are based on orders placed some time back (Yarbough and Yarbrough, 2002). On other hand, domestic exports become more attractive to foreign markets but quantities do not adjust immediately for the same reason. An increase in value of the imports against a constant or a small change in the value of exports results in a trade deficit in the short run. As time pass-by importers have enough time to adjust their import quantities with respect to the rise in prices while quantity demand for exports increases and this result in an improvement in the Trade balance (Kamoto, 2006).

3.2.2 The Elasticity Approach

The Marshall –Lerner condition states that the sum of the elasticities of demand for a country’s exports and of its demand for imports ( in absolute value) has to be greater than unity for a devaluation to have a positive effect on a county’s trade balance. If the sum is less than unity, a country can instead improve its balance of trade by revaluation (Solderstein, 1995). In other words we can say that the condition for depreciation to improve the Trade balance, for the exchange market to be stable and for international barter exchange to be stable, the sum of import and export (in absolute value) of a given country must exceed one.

As a devaluation of the exchange rate means a reduction in the price of exports quantity demanded will increase. At the same time, price of imports will rise and their quantity demanded will diminish. The net effect on the trade balance will depend on price elasticities. If goods exported are elastic to price, their quantity demanded will increase proportionally more than the decrease in price and total export revenue will increase, similarly if goods imported are elastic, total import expenditure will decrease. Both will improve the Trade balance. Empirically, it has been found that goods tend to be inelastic in short term, as it takes time consuming patterns to adjust to new prices (Bahmani-Oskoee and Ratha 2004). Thus, the Marshall-Lerner condition is not met, and devaluation is likely to worsen the trade balance initially. In the long term, consumers will adjust to the new prices and the trade balance will improve. This effect is called J-curve effect.

3.2.3 Mundell – Fleming Model

The Mundell-Fleming model is an economic model first set forth by Robert Mundell and Marcus Fleming. The model is an extension of IS-LM model. Whereas the traditional IS-LM model deals with economy under autarky (or closed economy) the Mundell-Fleming model tries to describe an open economy.

Mundell- Fleming (MF) model (1962) assumes there is a small open economy with unemployed resources, a perfectly aggregate supply curve, exchange rate expectations and perfect capital mobility. The exchange rate varies as a real output and fiscal deficit is inactive. Therefore this model deals with the impact of monetary policy on real output. This implies that expansion in the money supply will expand income which in turn leads to decline of the domestic interest which leads to capital outflow and exchange rate depreciation. This will through Marshall- Lerner condition, results in an improved trade balance (Ronald, 1988).

3.3 Empirical Literature Review

Many researches have been done to investigate the relationship between exchange rate and trade balance; here we provide some of them:

Doppler (1974) investigated the effect of exchange rate changes on the trade performance of four developed countries, namely France and United Kingdom, which devaluated and Germany and Netherlands which revaluated. His study covered the period 1973 to 1985; he examined the effect of exchange rate changes on the volume of exports and imports by removing seasonal and cyclical factors so as to isolate the impact of exchange rate and income on trade. He found that changes in the exchange rate induced notable changes in the volume of exports from each country. For the countries devaluing there was increase in export volumes and those revaluing there was a decrease. The effect on imports was found to be less notable and the author attributed this to inappropriate methodology. Both countries devaluing experienced an improvement in their trade balances and both revaluing experienced deterioration.

Bhagwati and Quitsuka (1974) conducted an extensive study on the impact of devaluation in 46 non-industrial countries during 1960s. They used selected quantitative indicators to determine the response of exports and imports. These countries were divided into three broad groups. The first group in all cases export earnings grew faster after devaluation. The second group containing 14 countries which had a strong link with the United Kingdom. The third group containing 15 countries, in the two groups of countries that devaluated in response to devaluation in their major trading partner, the response of the foreign trade sector was less pronounced compared to the first group.

Miles (1979) examined the relationship between devaluation and trade and balance of payments during the 1960s for a group of 14 developed countries, the balance of payments improved after devaluation. There was no support for the hypothesis that devaluation improves the trade of balance. He concluded that the adjustment to devaluate is essentially monetary in nature involving only portfolio stock adjustments.

Rose and Yellen (1989) studied US data for the period 1960 to 1985 by using J-curve effect they did not see the relationship between trade balance and exchange rate. However Moffet (1989) examined for the trade price (price of export and import) and the quantities (quantities of export and import) of the USA to determine whether J-curve exists or not from the period of 1967 to 1987 reported results indicated that dollar depreciation leads to import quantities decrease, but it simultaneous decrease in the quantities of export based on J-curve theory depreciation leads imports to decrease and export increase. Export decrease in this case, so it resembles of sine wave rather than a J-shape.

Rose (1991) reported the Marshall learner condition does not exist in five major OECD countries (UK, Canada, Germany, Japan, and USA) Her results showed insignificant relationship between trade balance and exchange rate, thus implying that devaluation could not improve trade balance in the long run. Rose (1991) predicted it would reveal significant through trade balance treated as exogenous with respect to the exchange rate.

Brada and Zhou (1993) examined the response of the trade balance of China to the real exchange rate using quarterly data for 1980:I to 1980:IV. Cointegration technique was applied in this study, he found that both in the short-run and long-run devaluation serves to improve the balance of trade, though showed the bulk of the response to devaluation occurs over one year period with no J- curve effect. Marwah and Klein (1996) find evidence of S-curve for both Canada and US utilizing disaggregated data in IV and OLS regression for the period 1977 to 1992, According to their results the trade balance initially declines after depreciation followed by trade balance improvement.

Bronner et al (1997) have provided estimates of positive long- run relationships between net foreign assets and the real exchange rate using a vanity of data. He shown the relation between external wealth and the trade balance within and across countries is related to rates of return on external assets and liabilities and the rates of output growth by controlling other determinants they established a negative long run association between the trade balance and the real exchange rate. Moreover they found that the trade balance coefficient is increasing in country size and they provided direct evidence that the relative price of non tradable co-moves with the trade balance even controlling for relative sectoral productivity.

Hernan (1998) Tested the short-run and the long-run exchange rate effects on trade balance, the case of Columbia. He found that the exchange rate do play a role in determining the short and the long equilibrium behavior of the Columbia trade balance. The estimation reported that there is one co integrating relationship between trade balance, exchange rate, money, and income. That is a long-run equilibrium relationship between those variables exists. The results also showed that the BRM or ML conditions were supported by the data. This implied that (real) evaluation improved the equilibrium trade balance. Moreover the positive effect of exchange rate evaluation of the trade balance seemed if accompanied by reduction of stock of money and increase in income with respect to the short-run estimates, estimations revealed a significant positive short-run relationship between the trade balance and the exchange rate.

Studies by Waane (2000) on real exchange rate and trade balance in Tanzania from 1967 to 1997 showed that exchange rate is positively related to trade balance and foreign balance is related to trade balance. This means that an increase in real prices of foreign exchange improves trade balance. Baharumshah (2001) employs an unrestricted VAR model for bilateral trade of Thailand and Malaysia with the US and Japan for period 1980 to 1996 he finds support for a stable and positive long-run relationship between trade balance and the exchange rate.

Boyd and Caporale (2001) using structural Cointegrations vector Autoregressive Distributed Lag (VARDL) models measured the real exchange rate on the balance of payment. They use the models for domestic and foreign output, the balance of trade and the real exchange rate. Small systems were estimated for eight OECD countries to investigate long-run Cointegration. They concluded by saying that, “although there is considerable heterogeneity, overall the results suggested that Marshall Lerner condition holds in the long-run with some degree of J-curve effects in the short-run. If in addition nominal devaluation can improve the trade balance, with obvious implications for policy makers.”

Fisher and Huh (2001) studying Exchange rates, trade balances and nominal shocks in G-7 they found that a nominal shock causes a real exchange to depreciate and the trade balance to improve in long run, which is Lane’s model when the income effect of a nominal shock dominates the substitution effect. They further showed that a positive aggregate supply shock causes output to increase and the real exchange rate to depreciate in each of the G-7 countries, both in short run and long run. Both effects where statistically significant tended to work in opposite directions on the trade balance over both the short and long run. Aristotelous (2001) also report an insignificant relationship between exchange rate volatility on the UK-US exports for the 1889 to 1999 period.

Wilson and Kua (2001) examined the relationship case between Singapore and USA. Their result indicated exchange rate does not have significant impact on the bilateral trade balance. Hacker and Hatermi (2002) looked at disaggregated bilateral data between the Czech Republic, Poland and Hungary with respect to Germany. They found evidence of a positive long-run relationship between the trade balance and the exchange rate for all three countries. The Czech Republic and Poland seem to possess characteristics that lead to the J-curve.

Lane and Milesi-Ferretti (2002) they examined the link between foreign asset position, the trade balance and the real exchange rate. They showed that the relation between external wealth and the trade balance within and across countries is related to the rates of return on external assets and liabilities, and the rate of output growth. By controlling other determinants they established a negative long run association between the trade balance and the real exchange rate. Moreover they found that the magnitude of the trade balance coefficient is increasing in country size and they provided direct evidence that the relative price of non-tradable co-moves with the trade balance, even controlling for relative sectoral productivity.

Brahmasrenere and Jiranyakul (2002) investigated the impact of real exchange rate on the trade balances between Thailand and its major trading partners. They used non linear model (modified by Reinhart 1995) whereby they had the results that the impact of real exchange rate on trade balance is significant in most cases. Therefore the generalized Marshall- Lerner condition seems to hold. Furthermore, the results showed that the real exchange rates played a more important role in the determination of bilateral trade balances than other factors. Since the real exchange rate played a major role in their study, they recommended a policy that prevents exchange rate misalignment. Policies that can neutralize the changes in nominal exchange rate and they further advise the introduction of relative prices to prevent further deterioration of the trade balance.

An electronic study by Arize, et al (2003) of a sample of ten LDCs (including South Africa) tested for a long-run Cointegration and used the error correction technique to model the short run dynamics of variables. They found that exchange rate volatility exerts a significant negative effect on export demand in both the short-run and long-run in most of the countries studied. However, South Africa was import exception where positive statistically significant exchange rate elasticizes were obtained. These results were similar whether nominal or real effective exchange rates were used and when ARCH residuals were used to measure exchange rate uncertainty.

The greater support for the negative hypothesis in the LDCs is altributed to the more limited hedging facilities and generally less developed financial services sector and infrastructure in such countries. The fact that South Africa has a relatively sophisticated foreign exchange rate market with variety of hedging facility readily available at low cost may help the anomally found in the study by Arize et al. The fact that the prices of a large proportion of South Africa’s export are determined in world markets and denominated in dollar might also help explain why exchange rate volatility has little effective on competitiveness and demand for such exports. Hence it is not all surprising that Arize et al found a positive association between the rand exchange and export volumes.

Liew, et al (2003) studied the relationship between real exchange rate and balance of trade based in ASEAN countries. They suggested that trade balance is affected by a real money rather than exchange rate Broda (2004) examines the panel data for 75 developing countries covering the periods between 1973-1996 using VAR model. He finds that there exists substantial impact of real shocks such terms of trade of a country on real GDP in the short term. He also suggests that negative shocks lead to larger real exchange rate changes in countries with flexible exchange rate regimes. .

Akbostanci (2004) examines the short-run and long-run behavior of the trade balance and the real exchange rate in a dynamic model using Turkish data. She suggests that, in the long-run, a real depreciation of exchange rate will improve the Turkish trade balance. Her findings are consistent with the long-run result of earlier study on Turkish by Brada et al (1997).

Klein and Shambaugh (2004) made a research on exchange rate volatility on Trade .they found a significant effect of a fixed exchange rate on bilateral trade between a base country and a country that pegs to it. Furthermore they found that the web of fixed exchange rate is effective only when these countries are part of a wider system as during the Bretton woods period .Their results suggested an economically relevant role for exchange rate regimes in trade determination since a significant amount of world is conducted between countries with fixed exchange rates.

Bhattarai and Armah (2005) examined the effect of exchange rates on the trade balance of Ghana, using annual time series data 1970 -2000 to estimate, trade balance as a function of the real exchange rate domestic and foreign incomes. Methods for analysis where Cointegration of both single equation models and VAR-errors correction models to confirm a stable long-run relationship between both export and import and the real exchange rate. They found that any nominal devaluation of cedi (Ghana’s currency) was bound to weaken the trade balance at the least in the short to medium term. In the long run the result show that a stable linear relationship existed among exports, import and trade balance, domestic and foreign income.

They further suggested that Ghana has no choice other than to adhere to the fundamentals of the foreign exchange rate to solve its perennial problems of deficit by applying prudent fiscal and monetary policies and exchange rate policies based on purchasing power parity. They added that those policy rules will also improve the confidence of consumers and investors in the economy and Ghana’s competitiveness in the global market. Using Cointegration technique, Hatemi and Irrandousts (2005) study showed Sweden did not satisfy Marshall-lerner condition. This might be due to the trade balance in Sweden is not sensitive in real exchange rate but only sensitive in changes in income.

Thorbecke (2006) indicated that the change in the exchange rate could affect trade within Asia. His empirical studies demonstrated an appreciation in Indonesia, Malaysia, and Thailand would decline export. Aziz and Li (2007) analyzed the dynamic changes of the export elasticity to real exchange rate from 1995 to 2006. They found that price elasticity of china’s exports increase over time. After decomposing export into non-processing and processing exports they showed that the price elasticity of processing export increases significantly while that of non-processing exports remains unchanged.

Monacelli and Perotti (2007) applied VAR techniques to estimate, for a series of OECD Countries, the effect of Government spending shocks on the real exchange rate, the trade balance and their movements with GDP and private consumption. First, they found that in all countries a rise in government spending induces real exchange rate depreciation and a trade balance deficit. Second, in all countries private consumption rises to a government spending shocks and therefore co-moves positively with the real exchange rate. Futhermore they found that if the elasticity of substitution between domestic and imported goods is sufficiently small, their model was successful in delivering the right co movement between the real exchange rate and the trade balance.

Yuen-Ling et al (2008), by using unit Root Tests Cointegration techniques, angle-Granger test vector error correction model (VECM) and impulse response analysis. They found a long–run relationship exists between trade balance and exchange rate. Other important variables that determine the trade balance such as domestic income shows a long-run positive relationship between trade balances and foreign income shows a long-run negative relationship in Malaysia in the period 1955-2006.

Shao (2008) examined the major factors that influenced the bilateral trade between Japan and the USA using quarterly data from 1980: 1 to 2006: IV .The Johansen and Julius results indicated three long-run relationships among five macro variables: Trade balance, domestic income, foreign income, net foreign assets and real exchange rate. He found that taking the valuation effect of the net foreign asset position into account, the final effect of the exchange rate changes on trade balance is undetermined. Although appreciation can reduce trade surplus in short-run, in a longer horizon, there is no stable relationship. He therefore recommended that there is no need to adjust exchange rate in order to improve trade balance between two countries.

Taguchi (2009) by using a Johansen multivariate co-integration analysis verified the existence of a stable long-run correlation between real exchange rate and trade balance in Malaysia, the Philippines and Thailand. They also found that simulation analyzes for those countries showed that the pre-crisis trend of RER had a negative impact on trade balance. Baek et al (2009) examined the dynamic effect of changes in exchange rates on bilateral trade of agricultural products between USA and its 15 major trading partners. Special attention was paid to investigate whether or not the J-curve hypothesis holds for USA agricultural trade. For this purpose, an autoregressive distributed lag (ARDL) approach to Cointegration was applied to quantify time-series data from 1989 to 2007. Results show that the exchange rate plays the crucial role in determining the short and long-run behavior of USA agricultural trade. However they found little evidence of the J-curve phenomena for USA agricultural products with the limited states major trading partners.

Ahmad (2009) showed that the joint appreciation of the Yuan and currencies of china’s major processing trade partners would be more effective in curbing the growth of china’s processing trade. However, the study did not analyze the sensitivity of processing imports to variations of exchange rate. Chung et al (2009) investigated this similar issue as Garcia-Herman over a relatively longer period between 1980-2006. They converted monthly data into quarterly by sample averages and estimate both processing exports and imports equations the dynamic OLS regression. Their empirical findings contradict the expectation of a convectional theory, indicating that china’s processing exports would increase 1.86% to 2.68% for every 1% real appreciations of the Yuan rather than decrease. Garcia-Herero and Koivu (2009) used co-integration techniques to estimate the long-run elasticity of china’s processing exports and imports to real exchange rates. Base on monthly time series data from 1994 to 2005 they showed that china processing exports would be expected to decrease 1.3% for every 1% appreciation of the Yuan and processing imports would decrease too when the Yuan appreciates.

Herve et al (2009) investigated the effect of real exchange rate on trade balance of Cote d’I voire using multivariate Cointegration tests and Vector error correction models with time series data covering the periods of 1975-2007. They found that there is a long-run relationship among trade Balance (TB), Real exchange rate (RER), and foreign and domestic incomes for cote d׀I vore. Estimated results also showed that the RER has significant positive influences for the considered period. The Granger causality test showed that the (RER) Granger caused the trade balance then, based on the estimates, the Marshall –Lerner condition in the Cote d’Ivoire’s data was explored by utilizing the impulse response Function (IFR) which traced the effect RER on the trade balance viewing the curve pattern.

Babecky et al (2010) finds a greater gap in real exchange rate misalignments with mostly pegged exchange rates systems and a closer gap to fundamental equilibrium points in countries with flexible exchange rates. Bailey et al (1987) also observe volatility impact in both nominal and real exchange rates of quarterly data they studies of seven OECD and four other countries. Qureshi and Tsangarides(2010) investigate on extended database with exchange rate classification for the impact of fixed exchange rate regimes increase trade indifferently to macro-policy announcements in the system of real action in practice.

Bakhromov (2011) estimates the effect of exchange rate volatility on the international trade in Uzbekistan during the 1999-2009 period. Results show that the real exchange rate volatility has substantial impact on the exports and imports of the country during the given period. Furthermore he used Johansen’s Cointegration framework, to test for the presence of unique Cointegrating vectors linking series such as exports(imports), foreign(domestic) income, relative export/import prices(proxied by real exchange rate) with the volatility of the real exchange rate in the long-run. Results show that increases in the volatility of the real exchange rate have significant negative effects on equations of exports and imports in the long-run dynamics. He also observed that improvements in the terms of trade, as exchange rate declines exist.

Xing (2011) analysed the role of processing trade in china’s bilateral trade balances and the impact of the Yuan’s appreciation on processing trade. The analyses were based on panel data covering china’s 51 major trading partners from 1993-2008. The empirical analyses showed that

(i)	Processing trade accounted 100% of china’s overall trade surplus and can explain most of china’s bilateral trade balances.

(ii)	China’s processing trade has a significant regional bias. While China has maintained a surplus with all G-7 countries in the processing trade, it has run a significant deficit with most of East Asian economies.

(iii)	East Asian economies are major sources and account 77% of china’s processing imports.

(iv)	The response of processing imports to the Yuan’s appreciation differs with that of normal trade. Specifically, a 10% real appreciation of the Yuan will reduce rather than increase China’s processing imports by 3.9%. Given that processing exports will decrease 9.6% for the same appreciation of the Yuan would have a very limited impact on China’s trade balance.

Adeniyi et al (2011) studied the existence of J-curve in four West African Monetary Zone namely. The Gambia, Ghana, Nigeria and Sierra Leone, they used quarterly data Cointegration technique, they found that Cointegration exists among trade balance, foreign income, the real effective exchange rate and domestic income in all countries. Their results seem to support the J-curve only in the case of Nigeria with Sierra Leone displaying the obverve ( no J-curve effect).

Gomez et al (2012) using multivariate Cointegration test for non stationary data and vector error correction models examined the determinant of trade balance for Argentina over 40-50 years 1962-2005 taking into account the short-run impacts of currency depreciation on the trade balance. They confirmed the existence of long-run relationships among the trade balance real exchange rate and foreign and domestic incomes for Argentina during different real exchange rate management policies.RER depreciation showed permanent improvements on trade balance when the currency board in the convertibility plan is included in the analyzed sample.

Cheng et al (2012) investigate the effects of the real exchange rate and income on USA tourism export revenue and import spending with quarterly data for the floating exchange period 1973 to 2010.They found that Depreciation raises USA tourism export revenue but does not affect import spending. USA tourists going abroad respond to income while foreign tourists going to the USA do not. This means that USA tourists are sensitive to income but foreign tourists to the USA are not, suggesting that foreign USA tourists rely on income while tourists spend wealth.

Overall, the evidence suggests that the J-curve is not an empirical regularity. For some countries the J-curve effect predominantly applies, for some it does not. The evidence supports the existence of a favorable stable long-run relationship between the trade balance and the exchange rate, with a few exceptions.

3.4 Summary

The main contribution of the empirical literatures reviewed has to great extent supported the theory which asserts that appreciation of exchange rate causes deterioration in the trade balance whereby depreciation of exchange rate causes improvement in the trade balance. This implies that a country faces two effects when devaluing its currency, first the price effect, this means that exports become cheaper measured in foreign currency and imports becomes expensive measured in domestic currency. Second the volume effect whereby the fact that exports become cheaper should increase the volume exports and the imports becomes more expensive should lead to a decreased volume of imports. The net effect depends upon whether the price or volume effect dominates.

CHAPTER FOUR

4.0 RESEARCH METHODOLOGY

4.1 Introduction

This chapter presents the theoretical and empirical methodology which was employed to answer the question addressed by this study. Section 4.1 explains how the real exchange rate, trade Balance and other variables are measured in this study followed by Section 4.2 which stipulates the model specification. The sources of data and definition of variables are discussed in section 4.3. The estimation techniques are discussed in section 4.4.

4.2 Measurement of Variables

This section discusses the measurement of real exchange rate and trade balance and other variables used by this study. The direct measurement of the real exchange rate which is based on purchasing power parity theory is discussed.

4.2.1 Real Exchange Rate Measurement

The estimation of real exchange rate is based on purchasing power parity theory. According to this theory the real exchange rate is represented algebraically as;

(1)

Where is the real exchange rate, represents the nominal exchange rate, stand for foreign price level, and denotes the domestic price level.

The study uses the domestic consumer price index and the foreign consumer price index as proxies for domestic and foreign prices respectively.

4.2.2 Measurement of Trade Balance

Trade balance is defined as the difference between the value of exports and the value imports (Colander 2004), this study following Baharumshah (2001) measured trade balance as the ratio of imports to exports. The use of this ratio has several advantages first, it is invariant to units measuring for exports and imports, and second the regression equation can be expressed in log-linear form or constant elasticity form.

4.2.3 Measurement of Other Variables

World income is obtained by adding GDPs for UK, USA, Japan, India, Spain, China, Canada, and France all in 2010 prices. The choice of these countries depended on the trade shares to Tanzania. (i.e. Tanzania’s major trading partners). Domestic income is proxied by GDP.

4.3 Model Specification

The analysis of data was to examine the relationships between Trade balance (dependent variable) and real exchange rate, GDP, domestic real income and world real income (which are regressor). The study follows Shao (2008), Herve et al (2009) and Bhattarai and Armah (2005) by estimating a single equation model treating real exchange rate, GDP (domestic real income) and real world income as independent variables and Trade balance as dependant variable. The model is modified to include dummies in order to account for structural changes such as major policy changes such as trade liberalization which led to a shift to more flexible exchange rates from 1986 onwards. Therefore the model is expressed as follows;

TB = β0+β1RER +β2TGDP + β3WGDP + β4SAP + ξ (2)

Where ξ represents error term which is independently distributed random variable with mean zero and constant variance. RER represents real exchange rate, TGDP represents the Tanzanian GDP (domestic income), WGDP represents real world income, SAP represents the structural adjustment dummy, with the value of 1 from 1986 onwards and 0 otherwise. TB represents the dependant variable (Trade balance). β0, β1, β2, β3 and β4 are parameters to be estimated.

Taking Logs on both sides we obtained the log-linear transformation equation which will now estimate the β’s as elasticities.

lnTBt =α0 +α1ln RERt +α2lnTGDPt +α3lnWGDPt + α4SAPt +Øt (3)

where ln represents the natural log operation and Ø is assumed to be a Gaussian white noise.

According to economic theory, a positive relationship exists between real foreign incomes and Trade balances, and therefore α1 is expected to be positive. Also, real exchange rate depreciation implies an increase in country competitiveness in the world market making exports cheaper to foreigners’ hence increasing demand for domestic exports and improving Trade balance. Therefore, α3 is expected to be positive. Nevertheless α2 and α4 are expected to be positive.

4.4 Data Sources

The study used secondary time series annual data for the period 1970 to 2010.The data were obtained from international financial statistics (IFS) published by the international monetary fund and world bank (econStats IMF World Economic Outlook), National accountancy of Tanzania published by the National Bureau of Statistics, Tanganyika Library, Bank of Tanzania (BOT), economic bulletins and operation reports for various years. The study did not involve sampling since as it involved the use of secondary data.

4.5 Estimation Techniques

For determining the relationship between real exchange rate and trade flows (exports and imports), the Cointegration approach was used. The Cointegration approach takes into account the existence of a long run linear relationship between dependent variable and explanatory variables producing a stationary long-run relationship among non-stationary variables. This approach involves various time series techniques such as stationarity test, Cointegration test and finally error correction model representation if the Cointegration is confirmed where Ordinary Least Square (OLS) method is applied.

4.5.1 Stationarity Test

Most macroeconomic time series data tends to be non-stationary. Therefore direct estimation of the model using OLS techniques tends to produce spurious regression results. To avoid spurious results it is vital to test for stationarity of the variables before examining for long-run relationship between variables.

The study used two unit root tests which are Dickey and Fuller (1971, 1981) test and Zivot and Andrew test. The reason of using Zivot and Andrew test is to take into account the structural breaks. It has been found that the Zivot and Andrew test is better than the Phillips Perron test because it endogenously determines the structural shift and avoids the risk of data mining that may arise if the break point is set exogenously by a researcher (Bernhard, 2005).

4.5.2 Cointegration Test

The next step is to test whether there is a long run linear relationship between the dependent variable and the explanatory variables. There are two methods of testing Cointegration namely Engle- Granger (1987) methodology and The Johansen (1988) test. Each method has advantages and disadvantages. Engle- Granger methodology is easily implemented and useful when dealing with small sample size. As a sample grows infinitely larger, it is possible to find that one regression indicates that the variables are cointegrated but when its order of variables are reversed (making one of the independent variables as dependent variable) indicates that the variables are not cointegrated. This is undesirable feature since the test for Cointegration should be invariant to the choice of variables selected for normalization. Another disadvantage is that, it involves two stages estimation therefore any error introduced in the first stage is carried on to the second stage. Furthermore, the method cannot test for the presence of multiple cointegrating vectors.

The Johansen (1988) Test solves the problems of Engle-Granger methodology as it is useful in large sample size and also uses maximum likelihood estimators which avoid the problem of two-stage estimators. In addition, the Johansen (1988) Test can test the presence of multiple cointegrating vectors. However, the Johansen test has two main limitations. First it is not easy to implement. Second, it is unreliable in small samples.

Since this study has only 40 observations, the Engle-Granger (1987) methodology was found to be an appropriate method to test cointegration.

4.6 Summary

This chapter presented the theoretical and empirical methodology which was employed to answer a question addressed by this study. The model which is used to estimate the relationship between trade balance and real exchange rate has been described. Furthermore, the chapter highlighted data sources, variables definition, and different estimation techniques employed by this study.

CHAPTER FIVE

5.0 ECONOMETRIC ANALYSES

5.1 Introduction

This chapter presents and discusses the empirical findings and analysis of the study. The chapter is divided into five sections. Section 5.1 presents the descriptive statistics analysis of the variables in the model while section 5.2 explains the unit root test. Section 5.3 describes Cointegration equation and error correction model (ECM). Section 5.4 presents ordinary least square results and diagnostic test, Section 5.5 presents discussion of results and Section 5.6 presents comparison with other studies.

5.2 Analyses Descriptive Statistics

The Trade balance has been increasing at average rate of 0.463870 while real exchange rate at average rate 430.1249 for the whole period under consideration. The range of all variables is from 0.220384 to 629955.4. The minimum growth rate is 0.463870 and the maximum growth rate is 427239.0. The median which is the data at the centre ranges from 0.451427 to 474679.8. All variables are positively skewed except World GDP. This implies that most of the values are on the right of the mean and few of them on the left. The normality of the variables can be observed by using Jarque-Bera and Probability values, which are insignificant (all probabilities are greater than 0.05)

5.3 Stationarity Tests (Unit Root Test)

Most of the time series data are non-stationary at levels thus before applying the Cointegration procedure all variables must be tested to check if the series are stationary or non-stationary and their order of Integration.

Table 5.1 Summary of the Descriptive Statistics of the Data

TB	RER	TGDP	WGDP
Mean	0.463870	430.1249	6983.609	427239.0
Median	0.451427	195.0600	6220.380	474679.8
Maximum	0.802185	1432.300	16258.62	629955.4
Minimum	0.220384	7.020000	3117.080	185268.2
Std. Dev.	0.142821	482.6178	3497.965	144421.6
Skewness	0.685999	0.691866	1.151771	-0.254981
Kurtosis	3.031749	1.969887	3.388646	1.629176
Jarque-Bera	3.217450	5.083737	9.322979	3.654501
Probability	0.200143	0.078719	0.009452	0.160855
Sum	19.01868	17635.12	286328.0	17516800
Sum Sq. Dev.	0.815918	9316797.	4.89 x 108	8.34 x 1011
Observations	41	41	41	41

Source: Eviews Estimations

The Augmented Dickey Fuller (ADF) unit root tests were carried out on the economic variables as required in the equations in order to determine whether the variables are stationary or not. ADF also ensures that the problem of serial correlation is reduced (Dickey and Fuller, 1979), and it takes into account higher-order auto regressive lags. The results reported in Table 5.2 shows that none of the variables were stationary in their log levels, implying that the variables are integrated of higher order other than I(0). The ADF test statistics for each of the variables are greater than the critical values at the conventional levels (1%, 5%, and 10%) which imply that the data have unit root.

Table 5.2: Unit Root Test Results

At Levels	At First Difference
Variable	t-Statistic	Order of Integration	t-Statistic	Order of Integration
LogTB	-2.638(0.0853)	(1)	-6.779*(0.0001)	I(0)
LogRER	-2.442(0.1302)	(1)	-7.205*(0.0000)	I(0)
LogTGDP	-3.574(1.0000)	(1)	-6.990*(0.0000)	I(0)
LogWGDP	-3.617(0.6054)	(1)	-4.639*(0.0001)	I(0)

NOTE: The null hypothesis is that the series are non-stationary and the critical values at 1%, 5% and 10% are -3.648, -2.958 and -2.612 respectively. The asterisks (***), (**) and (*) indicate rejection of the null hypothesis of non-stationary at 1%, 5% and 10% levels of significance at all levels of significance, respectively. The numbers in brackets are the probability values.

The presence of unit root requires the variables to be differenced, after differencing once all variables became stationary, implying that the variables were integrated of order one I (1). The critical value for each of the variables turned out to be less than the computed t-value thus concluding the time series data be stationary after differencing once. This result is consistent with other empirical work in macroeconomic literature.

5.4 Cointegration Test and Error Correction Model

5.4.1 Cointegration Analyses

Since it has already been established that all variables are integrated of order one, there is a possibility that the linear combination of variables may have long-run equilibrium linear relationship. The Engle-Granger two-step methodology was used to test existence of long run linear relationship. First Equation (3) was estimated by Ordinary Least Square (OLS). The Ramsey test was applied to test for model specification and the test shows that there is no omitted variable problem. Then the residuals are saved and ADF test was applied to examine if the residuals are stationary. According to Engle-Granger, if the residuals are stationary it is concluded that the variables are cointegrated. If the residuals are non-stationary then it is concluded that the variables are not cointegrated. The results of the test on residuals are reported in Table 5.3.

Table 5.3: Cointegration Test for Residual Estimation

Variables	ADF-Test	Cointegration
ECM	-4.390**	Accepted

From Table 5.3, the unit root test shows that the residuals are stationary at the 5% level of significance. This implies that the variables are cointegrated of order (1, 1) and error correction model can be used to determine the short-run dynamics of the model.

5.4.2 Error Correction Mechanism

The presence of cointegration implies that the variables have a long run equilibrium relationship. The error correction model is used to capture the short run dynamics and it includes lagged error correction term (which is the lag of residuals obtained from Equation 3) as one of the explanatory variables which act as an equilibrating error. The error correction model is presented as follows:

( 4 )

The estimation of Equation (4) was done using the general to specific approach. The final regression results were obtained by eliminating the insignificant variables. The results are presented in Table 5.4.

Table 5.4: Error Correction Model Results for Trade Balance The Dependent Variable

Variables	Coefficient	Std. Error	T-Statistic	Prob.
Constant	0.081	0.033	2.420	0.013
0.316	0.203	1.550	0.013
0.634	0.089	7.160	0.000
0.049	0.037	1.310	0.080
-0.350	0.128	-2.730	0.010
SAP	0.293	0.073	4.040	0.000
R-square = 0.7833, Adjusted R- square = 0.69 F-statistic=23.13(0.0000)

5.4.3 Diagnostic Test

The R-squared shows that 78 percent of variations in Trade balance are explained by the remaining explanatory variables. This is a good fit but further diagnostic tests (see Appendix II) were performed to ascertain the validity of the model. The Ramsey RESET test for model specification indicates that the model has no omitted variable problem. The Breusch-Godfrey LM test for serial correlation shows that serial correlation is not a problem. The Breusch-Pagan test proves that the error term is homoscedastic. Since the residual are well behaved, that is, they approximate a white noise process; we proceeded to the interpretation of the results in Table 5.4.

5.4.4 Interpretation of Results

The results reveal that all variables have the expected signs. The real exchange rate coefficient indicated a positive effect on trade balance and was significant at 1 percent level. The coefficient of real exchange rate is 0.316 which implies that a 10 percent depreciation of real exchange rate causes 3.2 percent improvement in trade balance. The results are consistent with economic theory which suggests that depreciation of exchange rate will increase country competitiveness in the world market which will eventually lead to improvement in trade balance.

The world GDP coefficient is 0.0488 and is statistically significant at 10 percent level. This implies that a one percent increase in world GDP will lead to 4.8 percent improvement in the trade balance. Furthermore the Tanzanian GDP coefficient is 0.634, implies that a percentage increase in domestic income will bring about a 6.3 percent improvement in trade balance.

The estimated error correction coefficient of the cointegration vector is -0.3502 and significant at 1%. The coefficient confirms that the variables are cointegrated and the error correction mechanism is stable, which implies that any departure from the equilibrium in the short-run will eventually converge to long run equilibrium state. It also implies that 35% of adjustment occurs annually. The SAP dummy was incorporated to capture the structural adjustments. The coefficient was 0.2937 and was significant at 1%. This implies that the structural adjustments reforms brought about 29% improvements in the Tanzanian trade balance.

5.5 Comparison with Other Studies

Various studies have been done to investigate relationship between exchange rate and trade balance, from which different results have been obtained. The aims of investigation are see the way how exchange rate can be used as a tool to affect the trade balance in a certain direction. However after a century of research in the field we still do not have a sharp theory about depreciation and appreciation on trade balance (Qiao, 2005). The empirical findings in this direction are also mixed (Koray and McMillan, 1998). The results showed exchange rate to be positively or negatively related to trade balance and in some cases, it was found to be insignificant. Here we provide few of them which resemble this study.

Miles (1979) examined the relationship between devaluation and trade and balance of payments during the 1960s for a group of 14 developed countries, the balance of payments improved after devaluation. There was no support for the hypothesis that devaluation improves the trade of balance. He concluded that the adjustment to devaluate is essentially monetary in nature involving only portfolio stock adjustments.

Brada et al (1993) examined the response of the trade balance of China to the real exchange rate using quarterly data for 1980:I to 1980:IV. Cointegration technique was applied in this study, he found that both in the short-run and long-run devaluation serves to improve the balance of trade, though showed the bulk of the response to devaluation occurs over one year period with no J- curve effect. Marwah and Klein(1996) find evidence of S-curve for both Canada and US utilizing disaggregated data in IV and OLS regression for the period 1977 to 1992, According to their results the trade balance initially declines after depreciation followed by trade balance improvement.

Studies by Waane (2000) on real exchange rate and trade balance in Tanzania from 1967 to 1997 showed that exchange rate is positively related to trade balance and foreign balance is related to trade balance. This means that an increase in real prices of foreign exchange improves trade balance. Baharumshah (2001) employs an unrestricted VAR model for bilateral trade of Thailand and Malaysia with the US and Japan for period 1980 to 1996 he finds support for a stable and positive long-run relationship between trade balance and the exchange rate.

Fisher and Huh (2001) studying Exchange rates, trade balances and nominal shocks in G-7 they found that a nominal shock causes a real exchange to depreciate and the trade balance to improve in long run, which is Lane’s model when the income effect of a nominal shock dominates the substitution effect. They further showed that a positive aggregate supply shock causes output to increase and the real exchange rate to depreciate in each of the G-7 countries, both in short run and long run. Both effects where statistically significant tended to work in opposite directions on the trade balance over both the short and long run. Hacker and Hatermi (2002) looked at disaggregated bilateral data between the Czech Republic, Poland and Hungary with respect to Germany. They found evidence of a positive long-run relationship between the trade balance and the exchange rate for all three countries. The Czech Republic and Poland seem to possess characteristics that lead to the J-curve.

5.6 Summary

This chapter explored the descriptive analysis and unit root characteristics of the data used in the analysis. The unit root characteristics of the data were examined out using ADF test unit root tests. It is found that the data are stationary in first difference. The analysis was followed by cointegration tests and an error correction model (ECM). The results obtained showed the existence of long-run relationship between the variables.

CHAPTER SIX

6.0 CONCLUSION AND RECOMMENDATION

6.1 Introduction

This chapter consists of four sections. Section 6.1 presents the summary of the study; section 6.2 discusses the finding of the study; section 6.3 presents policy implications and section 6.4 presents limitations of the study and areas for further research.

6.2 Summary of the Study

The purpose of the study was to investigate the impact of exchange rate on Trade balance for the period 1970 to 2010. The trade deficit which can be expressed as a ratio of export to import motivated the study. It has been observed that over years, there were depreciations but trade balance expressed as a ratio of export to import has never even reached a unity. We wanted to know whether depreciation has negative effect or positive effect on trade balance. The general objective being to examine the impact of Exchange rate on Trade balance and specific objectives were

To determine if there is a significant relationship between exchange rate changes and trade balance.

To examine if there is a significant effect of Domestic income on Trade Balance.

To examine if there is a significant effect of World income on Trade Balance.

6.3 Findings of the Study

This study attempts to offer evidence on the long- term relationship between exchange rate and Trade balance in Tanzania for the period 1970 to 2010. The test for stationarity using Augmented Dickey-Fuller (ADF) test proved that the variables used in this study are stationary, though not in levels, but in their first differences. The next step involved test for cointegration using the Engle granger Cointegration approach which proved the existence of cointegration. Under such circumstances, we employed the error correction model (ECM), since it offers more and better information compared to other data generation processes. The results point to a close long-term relationship between exchange rate and trade balance. We found that Exchange rate, world GDP, Domestic GDP and structural adjustments reforms have a positive relationship with a trade balance. The depreciation of exchange rate leads to improvement in trade balance.

6.3 Policy Implications

According to the findings of this study, the real exchange rate is positively related to the trade balance for the period 1970 to 2010 which mean depreciation improves the trade balance. Therefore depreciation is recommended, but policy makers and implementers should put in consideration of other effect of depreciation for instance, although depreciation improves the trade balance it accelerates the domestic price levels thus leading to inflation.

Furthermore Marshall-Lerner Condition should be observed which tells us that the condition for depreciation (appreciation) to improve (deteriorate) the foreign currency value of Trade balance is that the absolute sum of price elasticities of export and import is greater than one (Allen, 2006). According to finding of this study Tanzania GDP is positively related to the trade balance hence we recommend more effort in increasing production this will improve the trade balance.

6.4 Limitations of the Study

In this study we used GDPs of some countries as World GDP by considering that they were major trading partners with Tanzania, the model might have imperfections if a major trading partner is excluded, which might be the case as trading activities of Tanzania and its neighboring countries is increasing. Furthermore, the real exchange rate was against USA dollar, we did not put in consideration currencies of other countries, as Tanzanian shilling can be depreciating against one currency at the same time appreciating against another. Also can impair the model.

Another limitation can be due to inconsistence of the data used in the study, since we used secondary data covering the period 1970 to 2010, the consistence and reliability of data vary from one source to another. This is a problem facing all developing countries whereby the quality of data is normally low.

6.5 Area for Further Studies

The following Areas need further investigation on how they can improve Trade balance; Import duty and subsidies on some goods imported as they may have significant effect on trade balance, The link between International marketing and Trade balance, this may put Tanzania’s products on exposure, Human capital development on how to increase production, this may increase production and growth, Cost of production on both exports and imports and how they can affect Trade balance, Effect of Price on goods manufactured at home on Trade balance and How Tanzania should have high imports substitution to improve Trade balance by reducing import effects.

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APPENDICES

Appendix 1: Data Used in the Study

YEAR	Trade balance	Exchange rate	TGDP	WGDP
1970	0.790325418	7.14	3117.08	185268.22
1971	0.701797506	7.14	3247.37	193223.78
1972	0.802185224	7.14	3465.73	208670.68
1973	0.741908594	7.02	3571.66	225034.98
1974	0.535261298	7.13	3660.95	222483.69
1975	0.484063047	7.37	3869.17	229568.44
1976	0.68846729	8.38	4124.87	238581.63
1977	0.681334199	8.29	4141.44	249174.71
1978	0.417037963	7.71	4229.65	262364.27
1979	0.451427312	8.22	4352.73	275887.58
1980	0.406625922	8.20	4494.91	301583.05
1981	0.483191293	8.28	4549.41	314179.74
1982	0.394675683	9.28	4551.92	324556.94
1983	0.466114678	11.14	4511.68	334941.03
1984	0.454573708	15.29	4532.64	336044.42
1985	0.285112641	17.47	4712.91	372014.35
1986	0.369068254	32.70	4977.86	382901.03
1987	0.311964948	64.26	5288.08	398668.18
1988	0.334549908	99.29	5599.98	427083.39
1989	0.350792407	143.38	5811.17	450006.34
1990	0.242762723	195.06	6220.38	474679.76
1991	0.220384082	219.16	6349.26	490037.14
1992	0.275798701	297.71	6386.33	495074.08
1993	0.294074579	405.27	6463.37	497205.86
1994	0.346293929	509.63	6564.65	503005.19
1995	0.402904295	574.76	6799.04	513850.03
1996	0.565897964	579.98	7108.02	528660.89
1997	0.561313443	612.12	7358.6	538541.7
1998	0.405142284	664.70	7631.49	530464.26
1999	0.354785513	744.80	7900.88	531950.35
2000	0.43551477	800.40	8290.69	548161.15
2001	0.452792789	876.40	8787.95	550702.91
2002	0.544452475	966.60	9417.48	553999.26
2003	0.531516654	1,038.90	10065.99	564003.72
2004	0.538987328	1,089.10	10853.99	581489.74
2005	0.509049677	1,129.20	11653.91	595832.01
2006	0.408032868	1,253.90	12474.63	611564.05
2007	0.416657537	1,244.10	13341.54	629955.41
2008	0.415308529	1,196.30	14315.13	626976.12
2009	0.455980525	1,319.90	15274.82	595542.63
2010	0.4905522	1,432.30	16258.62	622866.81

Appendix 2: Tables

Table 2.1 Ramsey RESET test

F- Statistic	Probability
0.097682	0.759994

Table 2.2 White Heteroskedasticity Test:

F-statistic	2.883789	Probability	0.013470
Obs*R-squared	18.68378	Probability	0.21973

Table 2.3 Breusch-Godfrey Serial Correlation LM Test:

F-statistic	5.136606	Probability	0.011065
Obs*R-squared	9.303552	Probability	0.209545