Appreciation or overvaluation of exchange rates in times of capital flows and its impact on exports or even imports is a matter of policy debate. Against such a background, this paper examines empirical evidence of stationarity in the data on India’s bilateral real exchange rates with 16 of its major trading partner countries over a period of 5 decades (from 1960 to 2012). The results from the Lagrange multiplier (LM) unit root test with two structural breaks provide evidence of stationarity only for 9 countries. This is in contrast with the overwhelming evidence of stationarity in earlier studies. The rapid growth of international trade and capital flows particularly prior to the 2008 financial crisis and a concomitant shift in exchange rate regime may have significantly affected the behavior of India’s real exchange rate vis-à-vis some of the countries in our sample. This has implications for the Reserve Bank of India (RBI) to sustain its intervention pace on a continuous basis given the fear of rupee being overvalued. The associated liquidity injection will have important implications for the conduct of India’s monetary policy.
There was a major shift in India’s economic policy paradigm in 1991. It conducted market-oriented reforms, opened up the economy to international trade and foreign investment, and moved to a market-determined exchange rate regime. These developments have an important bearing on the behavior of India’s real exchange rate vis-à-vis its major trading partner countries. With the growing importance of trade and foreign investment for India’s economic growth and development, it is critical to know whether disturbances to real exchange rates have a permanent or a transitory effect. Thus, this paper examines the stationarity of India’s bilateral real exchange rate with 16 of its major trading partner countries from 1960 to 2012, extending the works of Narayan [
Bilateral nominal exchange rate is the value of one currency expressed in terms of another currency. When this exchange rate is adjusted for the differences in prices between the two countries, we have bilateral real exchange rates. The purchasing power parity (PPP) hypothesis has been the major theoretical framework for examining the dynamic behavior of real exchange rate. This hypothesis, based on the law of one price, suggests that, “once converted to a common currency, national price levels should be equal” [
Numerous empirical studies on the PPP hypothesis have been conducted and published over last several decades. The results have been mixed: while some studies find evidence to support the hypothesis, others do not. Rogoff [
Using Lagrange multiplier (LM) unit root test with two breaks, Narayan [
There have been significant increases in India’s trade with the rest of the world and in foreign investment from abroad since 2000. For example, the GDP share of trade increased from about 21% in FY2000 to about 37% in FY2015. Net inflows of foreign direct investment (FDI) as a share of GDP rose from 0.75% in FY2000 to about 3.5% in 2008 and then dropped to about 1.5% in FY2015. Furthermore, inflows of foreign institutional (portfolio) investment (FII) as a share of GDP rose from 0.01% in FY2000 to about 0.33% in 2008 and further to about 1.5% in FY2015. The growth of trade and capital flows is expected to have affected the behavior of India’s real exchange rate in recent years. Furthermore, there have been important differences in the evolution of international economic and financial relationship with different countries around the world. Consequently, the relative shares of different countries in trade investment flows have changed over the years. For example, in the mid-1990s, the US accounted for the largest share of imports into India. Currently, China holds that distinction. During the same period, the US has been the largest destination for India’s exports although the share has declined from about 20% in 1996-97 to about 13% in 2013-14. Against this backdrop, in this short paper, we reexamine the evidence of stationarity in India’s real exchange rate with the 16 countries in Narayan [
The rest of the paper is organized as follows. Section 2 briefly discusses data and methodology. In Section 3, we present our main empirical results. A discussion of the results and their implications is included in Section 4. The last section concludes.
We obtain annual data on nominal exchange rates and consumer price indices (CPIs) for India and 16 countries from 1960 to 2012 from the World Development Indicators (WDI) database, compiled and maintained by the World Bank1. The base year for CPI is 2005. The countries are: Australia, Canada, France, Germany, Hong Kong, Italy, Japan, Korea, Malaysia, New Zealand, Pakistan, Philippines, Sri Lanka, Thailand, the United Kingdom, and the United States. The nominal exchange rates are in terms of the number of domestic currency per unit of US dollar (USD). We divide a country’s nominal exchange rate by India’s nominal exchange rate to obtain the bilateral nominal exchange rate in terms of that country’s currency per unit of Indian Rupee (INR)2. We then multiply this by relative price between India and the country under consideration (India’s CPI divided by the other country’s CPI) to calculate the corresponding bilateral real exchange rate3.
The choice of these countries is primarily dictated by the availability of data4. These 16 countries together accounted for about 29% of India’s total trade in 2011-2012. Further, 9 out of these 16 countries are among the top 25 trading partners of India5. The US alone accounts for more than 11% of India’s exports, 5% of imports, and more than 7% of total trade.
Introducing structural breaks in unit root tests has been a way of resolving the so-called PPP puzzle, the inability to find evidence of stationarity of real exchange rate. It also makes intuitive sense to consider such breaks particularly when the sample period has reasonable length. Since there have been changes in the policy paradigms and exchange rate regimes in India, it is but natural to expect structural breaks in its real exchange rate series. Therefore, like Narayan [
, (1)
where rt is the bilateral real exchange rate; Zt is a vector of exogenous variables and εt is iid N(0, σ2). We allow for breaks in level as well as in trend and, therefore,
where Djt = 1 for
where
The grid search is conducted over the trimming region (0.15T, 0.85T) where T is the sample size. Critical values are provided by Lee and Strazicich [
TB1 | TB2 | f | Constant | D1t | D2t | DT1t | DT2t | k | |
---|---|---|---|---|---|---|---|---|---|
Australia | 1974 | 2004 | −0.835 [−4.56] | 0.004** [2.09] | 0.001 [0.34] | −0.002 [−0.54] | −0.007*** [−2.98] | 0.004** [2.59] | 7 |
Canada | 1975 | 1988 | −0.909** [−6.30] | 0.001 [1.21] | −0.017*** [−8.23] | −0.004* [−1.98] | 0.003** [2.65] | −0.006*** [−5.24] | 6 |
France | 1979 | 1990 | −1.060** [−5.82] | 0.024*** [3.47] | −0.051*** [−2.79] | 0.030* [1.70] | 0.024*** [3.52] | −0.061*** [−5.31] | 8 |
Germany | 1979 | 1994 | −1.025* [−5.31] | 0.004* [1.90] | −0.005 [−0.96] | 0.001 [−0.17] | 0.006*** [3.16] | −0.008*** [−3.05] | 7 |
Hong Kong | 1975 | 1996 | −0.719* [−5.52] | 0.037*** [3.22] | −0.059*** [−3.23] | 0.018 [1.00] | −0.004 [−0.43] | −0.028*** [−2.97] | 7 |
Italy | 1979 | 1989 | −1.151** [−6.00] | 0.506 [0.45] | −9.008** [−2.03] | 5.955 [1.31] | 10.953*** [4.72] | −15.603*** [−5.23] | 8 |
Japan | 1977 | 1992 | −1.206 [−5.15] | 0.039 [0.23] | −1.945*** [−4.80] | −0.328 [−0.92] | 0.823*** [5.22] | −0.658*** [−3.22] | 7 |
Korea | 1974 | 1997 | −1.542** [−6.07] | 19.040*** [4.98] | 14.108*** [3.72] | 8.29*** [3.05] | −27.78*** [−5.71] | 1.121 [1.23] | 8 |
Malaysia | 1989 | 1999 | −0.491 [−3.92] | −0.001 [−0.51] | 0.011* [1.76] | −0.002 [−0.30] | −0.008** [−2.66] | 0.011*** [3.21] | 1 |
New Zealand | 1981 | 1990 | −0.683** [−5.98] | 0.001 [0.82] | −0.005 [−1.43] | −0.006 [−1.60] | 0.001 [0.83] | −0.002 [−1.41] | 2 |
Pakistan | 1989 | 1999 | −1.044 [−4.95] | −0.005 [−0.21] | 0.171 [1.37] | −0.109 [−0.89] | −0.147*** [−2.91] | 0.188*** [3.20] | 5 |
Philippines | 1974 | 1999 | −1.132 [−5.08] | 0.411*** [4.39] | 0.376** [2.15] | −0.105 [−0.782] | −0.554*** [−4.95] | 0.199*** [3.54] | 8 |
Sri Lanka | 1976 | 1990 | −1.096*** [−6.59] | −0.134 [−1.51] | −0.794*** [−2.69] | −0.143 [−0.55] | 1.185*** [5.51] | −1.21*** [−6.08] | 5 |
Thailand | 1991 | 1999 | −0.793 [−5.11] | 0.080*** [3.38] | 0.077 [1.14] | −0.049 [−0.76] | −0.099*** [−2.70] | 0.050* [1.69] | 3 |
United Kingdom | 1976 | 1995 | −1.621*** [−7.23] | 0.003*** [3.90] | 0.004** [2.55] | −0.000 [−0.09] | −0.004*** [−5.39] | −0.001 [−1.533] | 6 |
United States | 1979 | 1995 | −1.363 [−5.00] | 0.003*** [2.86] | 0.007*** [2.67] | −.001 [−0.25] | −0.006*** [−4.65] | 0.001 [0.76] | 5 |
Critical values for the LM test | |||||||||
λ2 | |||||||||
0.4 | 0.6 | 0.8 | |||||||
λ1 | 1% | 5% | 10% | 1% | 5% | 10% | 1% | 5% | 10% |
0.2 | −6.16 | −5.59 | −5.27 | −6.41 | −5.74 | −5.32 | −6.33 | −5.71 | −5.33 |
0.4 | −6.45 | −5.67 | −5.31 | −6.42 | −5.65 | −5.32 | |||
0.6 | −6.32 | −5.73 | −5.32 |
Notes: ***, **, *denote statistical significance at the 1%, 5%, and 10% levels, respectively. The critical values are taken from Lee and Strazicich [
test is able to reject the unit root null at least at the 10% level for nine countries. Note that Narayan [
As for the break dates, the first structural break occurred between the oil price shocks of 1973 and 1979 for 12 countries. For Malaysia, Pakistan and Thailand, the first break occurred close to India’s BOP crisis in 1991. The second break occurred after India’s economic reform for 11 countries. For Canada, France, Italy, New Zealand, and Sri Lanka, we find the second break just before the crisis of 1991. However, without further investigation, we cannot suggest that these particular events had anything to do with the structural breaks. The fact that there are wide variations in the break dates seems to suggest a significant role for country-specific factors, study of which is beyond the scope of this short note. Note that Hegwood and Nath [
As it is clear from our discussion above, both trade and capital inflows have been growing faster than GDP during the last decade or so. The behavior of India’s bilateral real exchange rates has been affected by the evolution of trade, capital flows, and movements of relative prices in specific countries. Without a formal analysis, we briefly discuss some of these developments below.
India experienced large inflows of capital well in excess of its current financing needs (net of capital account balance minus current account balance) over the years except in 2009 ($-20.5 billion) and 2012 ($-10.4 billion), when foreign investors were skeptical about global economic recovery. This resulted in high domestic credit and monetary expansion, boom in capital markets and other asset prices, and in general excess domestic demand leading to macroeconomic and financial instability in the domestic economy.
all, capital account transactions grew much faster (average growth of 53%) relative to current account transactions (19.0%).
The accommodative monetary policy in advanced economies, primarily in the US, after the financial crisis was also mirrored in the strong base money expansion during 2008-12 with an average growth rate of 12.4%, much higher than the expansion at the rate of 2.4% during the previous five years: 2003-07. As a consequence, inflation accelerated. These developments are intricately related to the exchange rate movements that are likely to vary across countries depending on the nature of their relationships with India in terms of capital and current account transactions and movements in relative prices8.
In FY2015, excess capital flows (net of capital account balance minus current account balance) were $62 billion (in FY16 they declined to $19 billion). This provides multiple challenges for the Reserve Bank of India (RBI). First, RBI would need to sustain its intervention pace on a continuous basis, given the constant fears of rupee getting overvalued (that is substantiated by the evidence of non-stationarity and structural breaks)9. Such real appreciation has likely resulted in loss of competitiveness of our exports in FY2015. Second, such intervention will have attendant liquidity injection which will have several ramifications for RBI in terms of a faster than anticipated reserve money growth and hence money supply.
This paper examines empirical evidence of stationarity in the data on India’s bilateral real exchange rate with 16 of its major trading partner countries from 1960 to 2012, extending the study by Narayan [
The authors would like to express their gratitude for the editorial comments that have been useful in revising the paper. The opinions expressed in this paper are those of the authors and do not necessarily reflect those of theState Bank of India or other members of its staff.
Ghosh, S.K. and Nath, H.K. (2016) Are Bilateral Real Exchange Rates Stationary? Revisiting the Evi- dence from India. Theoretical Economics Letters, 6, 1196-1204. http://dx.doi.org/10.4236/tel.2016.65113