PERSONAL DISPOSABLE INCOME AND IMPORT EXPENDITURE: AN EMPIRICAL STUDY ON INDIA Sanjay Kumar Mangla11 2
Tapan Kumar Nayak2
Abstract Volume of international trade plays a very crucial role in the economic development of the country as it directly affects the ‘balance of payment’. The present study investigates the behavior of Indian aggregate imports during the period 1991-92 to 2007-08. The paper is designed on the basis of two important objectives, to estimating the value of ‘Marginal Propensity to Import’ (MPI) and to know the sensitivity of imports for ‘Personal Disposable Income’ (PDI). In the empirical analysis, ‘Ordinary Least Square’ method has been used and imports were found to be very sensitive for PDI in India during post reform period where MPI was estimated to be 0.2955 which means that during this period Indians spent 29.55 % of the change in their PDI on imports.
1. Introduction International trade is very important for the industrial and overall economic growth of any economy especially developing economies like India. Prior to economic reforms in 1991, volume of import and export was very less in India due to heavy trade barriers like high custom duties, import quotas, tariff etc. But with the changing global pattern, India also adopted the path of economic reforms (such as liberalization, privatization and globalization) and trade reforms (such as liberalized trade policies etc.). These reforms paved the way to the economic progress of the country and led to increase in the volume of international trade. In order to determine the factors affecting international trade, several theories (such as absolute cost advantage theory, comparative cost advantage theory, modern theory of international trade etc.) were propounded in the economic literature. Imports and exports of a country depend upon many quantitative and qualitative factors such as national income/GDP, exchange rate, unit price of imported goods, domestic price of imported goods, foreign exchange reserves, trade relation between two countries etc. Estimation of import function or relationship between import and its
1
Lecturer, Institute of Management Studies – Ghaziabad, Uttar Pradesh, India. Email:
[email protected] 2
Associate Professor, Institute of Management Studies – Ghaziabad, Uttar Pradesh, India. Email:
[email protected]
1
determining factors has been a popular area of research in economic literature since recent decades. The present paper is concerned with the econometric modeling of classical import function or relationship between import and personal disposable income (PDI, the amount of income left to an individual after taxes have been paid, available for spending on goods and services and saving.),ceteris peribus, using Ordinary Least Square method in India in post reform period. The paper also deals with estimation of marginal propensity of import (MPI, the change in imports due to change in PDI) in the country in post reform period as reliable estimates of MPI are very important for policy makers in a number of areas such as exchange rate policy, fiscal implications of trade liberalization programmes and calculation of optimal taxes etc. 2. Literature Review Import function construction usually appears as a part of balance of payment block of macroeconomics/macro econometric models and it has been an important area of research in economic literature since beginning. Classical economist postulated a linear import function that describes a positive relationship between national income and imports of a country ceteris peribus which states that imports are an increasing function of national income i.e.
M f (Y d ) and
M 0 Y
Where M = import Y d = personal disposable income Since then several studies (such as Deyak (1989) for United States, Elliot, Kwack and Tavlas (1986) for Kenya, Brooks and Gibbs (1994) for New Zealand, Ho (2004) for Macao, Ghorbani and Motallebi (2009) for Iran etc.) have been conducted in various countries in order to find the relationship between imports and its determining variables like GDP, unit price of imported good, domestic price of imported good, foreign exchange reserves etc. Few attempts have also been made in India to estimate aggregate import demand function for the country such as Sinha (1996), Dutta and Ahmed (2001) and Dash (2005) etc. Sinha (1996) investigated the behavior of Indian aggregate imports for the period 1960-92. He did not find any empirical evidence in favor of the existence of any cointegrated relationship among the variables used in the aggregate import demand function. However, Dutta and Ahmed (2001) examined the behavior of Indian aggregate imports for the period 1971-95. The study had two objectives first, whether there existed a long run relationship between India’s aggregate import volume and its major determinants such as relative prices, 2
GDP and dummy variables, and second to investigate the effect of India’s import liberalization policy on its import demand. Using cointegration and error correction modeling approach developed by Johansen (1988 and 1991) and Johansen-Juselius (1990, 1992 and 1994), they found import volume to be cointegrated with relative import price and real GDP and import demand was largely explained by real GDP was generally less sensitive to import price change. In addition, they found that import liberalization had little impact on import demand. Dash (2005) underscored the behavior of aggregate import demand function of India for the period 1975-2003. Using yearly time series data, he used Johansen-Juselius (1990, 1992 and 1994) multivariate cointegration technique to find that whether any cointegrating relationship exits between import demand and macro economic variables such as gross domestic product (GDP), unit value of import price, price of domestically produced goods and foreign exchange reserves. The author have also found that more than one cointegrating relationship exits among these variables and India’s Import demand is dominated by price of domestically produced goods, GDP, lag of import and foreign exchange reserves. Moreover the above studies have tried to estimate the import function using cointegration technique but no one of them emphasized on estimating the value of MPI which is very important. Therefore in this background, this paper has estimated the value of MPI in India during post reform period.
3. Objectives The paper has following objectives: 1. To estimate the relationship between import and personal disposable income in India in post reform period. 2. To estimate marginal propensity to import and to determine at what extent personal disposable income affects imports in India.
4. Empirical Model In order to measure the spending of personal disposable income (PDI) on imports, an attempt has been made to design the empirical model by taking two variables (imports as dependent and PDI as independent). In its simplest form, macroeconomic theory postulates an import function which states that there exists a positive relationship between imports and National income of a country, ‘ceteris 3
peribus’. Here, PDI has been taken as a representative variable for national income. Economic theory provides the following information with respect to import function. M = f (Yd) Where M = imports Y = PDI
However, economic theory does not specify the mathematical form (linear or non-linear) of the import function. It has been assumed in the present research model that both, imports and PDI, are linearly related, as follows: M i = b0 + b1Yi d ................................... (1)
Where Mi = imports in ith period Yi = PDI in ith period b0 = intercept term/autonomous imports b1 = slope of the function/marginal propensity to import (MPI) MPI is the charge in imports due to the changes in PDI and calculated by the M formula . Y d The simple function presented above states that changes in imports are solemnly due to changes in PDI. But practically it is impossible as imports of country are affected by other factors too, like exchange rate, import duties, prices of imported goods etc.Therefore, in order to take into account the effect of these variables also on imports of a country, a random term ui is introduced in the mathematical model and we get the econometric model that presents the true relationship between imports and PDI. the true relationship between M and Yd is M i = b0 + b1Yi d ui ……………………. (2)
and the true regression line is E (Mi) = b0 + b1Yi d ............................... (3) the estimated relationship is M i = bˆ0 + bˆ1Yi d ei ................................ (4)
4
the estimated relationship is Mˆ i = bˆ0 + bˆ1Yi d ....................................... (5)
Where
Mˆ = estimated value of M given a specified value of Yd bˆ = estimate of the true intercept term 0
bˆ1 = estimate of the true parameter b1
e = estimate of the true value of the random term ui The true and the estimated regression lines are shown in figure 4.1 Fig. 4.1 PDI Mˆ i = bˆ0 + bˆ1Yi (Estimated line regression line) E ( M i ) = b0 + bY i i (True regression line)
O
M
In order to estimate the numerical values of the true parameters b0 and b1, one should have all the conceivable values of imports imported at all conceivable values of PDI, which of course is impossible. Therefore, a sample of observed values of imports and level of PDI over some period of time (in present research work, time period is form 1991-92 to 2007-08 for India) is taken and an attempt is made to obtain best possible estimate of the true import PDI function. However, the snag in this procedure is that from a given sample one may obtain an infinite number of estimated regression lines, (i.e. import functions) by assigning different values o the parameters b0 and bi. Therefore, to remove this snag, the estimated regression line has been chosen on the basis of the Least Squares Criterion. Which requires that the regression line be drawn in such a way as to minimize the sum of the squares of the deviations of the observation from it? Hence, in order to minimize the effects of random term u (i.e. factors exchange rate, import duties etc.) on imports, the deviations of the sample observations from the true import function n 2 ei line, are squared and sum of the squared of the deviations i 1 is minimized.
Now the residual deviations (e’s) expressed in terms of the observed values of imports (M) and PDI (Yd).
5
Fig. 4.2 M Mi ei Mˆ i
Mˆ i
O
Yi
Mˆ i = bˆ0 + bˆ1Yi d
Yd
In fig. 4.2, the estimated relationship is Mˆ i = bˆ0 + bˆ1Yi d . If bˆ0 and bˆ1 are numerically known, from the estimated line we can obtain a prediction of M1 that is, an ‘estimated’ value of the
dependent variable (Mi) which corresponds to a given value of the explanatory variable Yi d . However, the actually observed value of the dependent variable which corresponds to Yi d , is Mi, and not Mˆ i as the line predicts. In other words, the actually observation of M may not lie on the estimated line. It is apparent that the equation does not predict the values of the dependent variable with perfect accuracy. However, ei denotes the difference between the observed value Mi and its estimated value Mˆ i that is ei M i Mˆ i ........... ............................... (6)
Substituting the value of Mˆ i ei M i bˆ0 – bˆ1Yi d ................................. (7)
Squaring these deviations and taking their sum n
n
e 2 i
i 1
i 1
M i Mˆ i
2
n
Mˆ
i
bˆ0 – bˆ1Yi d
i 1
2
........ (8)
The sum of the squared residual deviations is to be minimized with respect to bˆ0 and bˆ1 . Following the minimization procedure we get the normal equations as follows: M nbˆ0 bˆ1Y d YM bˆ0 X bˆ1X 2 6
Solving the normal equations for bˆ0 and bˆ1 . We obtain the least square estimates as Y 2 M Y Y d M bˆ0 2 nY d (Y d ) 2 nY 2 M Y d M bˆ1 2 n Y d ( Y d ) 2
and values of the estimated parameters expressed in deviations of the variables from the means are: bˆ0 M bˆ1Y d
y d m bˆ1 i 2 i yid
Where yi Yi d Y
d
mi M i M
5. Empirical Analysis In order to calculate the value of MPI, Ordinary Least Square model is used and the regression analysis properties of the data on import and PDI in India (see annexure) during the period 199192 to 2007-08 are: Table 1 PDI and Import Expenditure: Regression Statistics Dependent Variable: Mi Df: 16 Total Observation: 17 Variables
Coefficients
Standard Error
t-Statistics
Significance level
Intercept
-202010.3989
46564.34108
-4.33830683
1%
Yid
0.295494467
0.023983248
12.32086923
1%
R-Square
Adjusted R-Square
0.91
0.90 7
In the above empirical analysis, aggregate imports in the country during post reform period are found significantly elastic to the PDI as MPI is found to be 0.2955.
6. Summary and Conclusion International trade plays a very important role in the economic development of any economy. To have sound volume of international trade of any economy, it is very important to know that which factors determine it. Several studies have been done to estimate import function of different countries to find that which factors and at what extent affect import of a country. In this paper, relationship between import and personal disposable income has been estimated in India during post reform period. To estimate this relationship Ordinary Least Square method has been used. It has been found that imports were significantly explained by personal disposable income. Marginal propensity to consume was found to be very high i.e. 29.55 % that reflects that Indians spent 29.55 % of the increase in their personal disposable income on imports during post reform period. The result shows that Indians spent a good amount of their PDI on imports. The direct impacts of which are that first it adversely affects the Balance of Payments of the country and second it leads to less demand for the products produced by domestic industries which becomes a reason for unemployment in the country therefore Government should take measures (like improvement in the quality of the domestic products, provide subsidies to domestic industries etc.) to protect domestic industries.
7. References Brooks, R. and Gibbs, D., 1994, “A Model of the New Zeland Economy”, Economic Modelling, 11(1), pp. 5-86. Dash, A.K., 2005, “An Econometric Estimation of the Aggregate Import Demand Function for India”, IBRC Athens. Deyak, T.A., Sawyer, W.C. and Sprinkle, R.L., 1989, “An Empirical Examination of the Structural Stability of Disaggregated U.S. Import Demand”, The Review of Economics and Statistics, 71, pp. 337-341. Dutta, D. and Ahmed, N., 2001, “An Aggregate Import Demand Function for India: A Cointegration Analysis”, The University of Sydney, The School of Economics and Political Science Working Paper.
8
Elliot, J., Kwack, S.Y. and Tavlas, G.S., 1986, “An Econometric Model of the Kenyan Economy”, Economic Modelling. Ghorbani, M. and Motallebi, M., 2009, “Application Pesaran and Shin Method for Estimating Iran’s Import Demand Function”, Journal of Applied Sciences, 9(6), pp.1175-1179. Gujarati, D.N. and Sangeetha, 2007, “Basic Econometrics”, Fourth Edition, Tata Mcgraw-Hill, New Delhi. Ho, W.S., 2004, “Estimating Macao’s Import Demand Functions”, A working Paper of Monetary Authority of Macao. Koutsoyiannis, A., 2007, “Theory of Econometrics” Second Edition, Palgrave Macmillan, London. Sinha, D., 1996, “An Aggregate Import Demand Function for India”, Rivista Internazionale di Scienze Economiche e Commerciali, 43 (1996), pp. 163-173.
9
Annexure Macroeconomic data on import and personal disposable income (PDI) for India during post reform period. Volume of Import and PDI in India (Rs. Crore) Year Import PDI 1991-92 47850.8 531515 1992-93 63374.5 618587 1993-94 73101 716964 1994-95 89970.7 842261 1995-96 122678.1 959733 1996-97 138919.7 1145206 1997-98 154176.3 1263982 1998-99 178331.9 1474404 1999-00 215236.5 1617965 2000-01 230872.8 1773250 2001-02 245199.7 1954839 2002-03 297205.9 2064839 2003-04 359107.7 2282148 2004-05 501064.5 2495015 2005-06 660408.9 2806427 2006-07 840506.3 3182710 2007-08 1012311.7 3592172 Source: Handbook of Statistics on Indian Economy-2009, RBI, Mumbai
10
