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Have Economic Reforms Affected Exchange Rate Pass-Through to Prices in India?

This paper examines the behaviour of exchange rate pass-through to domestic prices in India after the reforms initiated in the early 1990s. Unlike observed in several countries, it finds a rise in exchange rate pass-through to domestic prices until recent years. Besides economic factors typically associated with economic liberalisation, the persistence of higher inflation is an important factor for the rise in pass-through.

SPECIAL ARTICLEEconomic & Political Weekly EPW april 19, 200871Have Economic Reforms Affected Exchange Rate Pass-Through to Prices in India?Jeevan Kumar KhundrakpamThis paper examines the behaviour of exchange ratepass-through to domestic prices in India after the reforms initiated in the early 1990s. Unlike observed in several countries, it finds a rise in exchange rate pass-through to domestic prices until recent years. Besides economic factors typically associated with economic liberalisation, the persistence of higherinflation is an important factor for the rise in pass-through. Amacroeconomic puzzle of the 1990s is the phenomenon of low inflation despite episodes of large currency deprecia- tion in several countries. In the cross-country context, this is shown to be the results of the low global inflationary environ-ment itself [Taylor 2000; Choudhri and Hakura 2001;Gagnon and Ihrig 2004]. Several other factors such as exchange rate volatility, import penetration, openness, import composition, trade distortions, transport costs and income have also been identified as important determinants of pass-through [Goldfajn and Werlang 2000; Campa and Goldberg 2004 and Frankel et al 2005]. With economic reforms, these macroeconomic variables determining exchange rate pass-through undergosubstantial transformation during the transition. In India, since the early 1990s economic reforms were initiated on several fronts and have led to a market determined exchange rate, full convertibility in the current account, a substantial reduction in peak and weighted average tariff rates, abolition of import licensing and quantitative restrictions, encouragement of foreign investment through liberalisation and simplifying pro-cedures, abolition of industrial licensing, allowing private sectors in areas earlier reserved for the public sector, decontrol of inter-est rates, reduction in pre-emption of banking resources and enforcing capital adequacy and prudential norms, government borrowing at market rates and discontinuation of automatic mon-etisation of deficit, and gradual liberalisation of administrative price control mechanism on a number commodities. Have the economic reforms affected the exchange rate pass-through to domestic prices in India? Do we observe the same declining phenomenon as in several countries? Currently, there is not much literature on India. The cross-country studies which have included India do not indicate temporal behaviour. This paper, using monthly data further investigates the behaviour of exchange rate pass-through to domestic prices during the post-economic reforms period. The rest of the paper has six sections. Section 1 provides a review of the literature to identify factors determining pass-through. In Section 2, the data issues and the stylised facts are briefly discussed. The empirical framework is laid out in Section 3 and the results are presented in Section 4. Section 5 provides a conjectural explanation for the observed trend in pass-through. The final section summarises.1 What Determines Pass-Through? In the traditional open-economy macroeconomic models, under purchasing power parity (PPP) assumption, exchange rate pass-through to domestic prices is always immediate and This is a revised version of the paper published as BIS Working Paper 225 and which is available in the BIS web site The views are personal.Jeevan Kumar Khundrakpam ( is with the Reserve Bank of India.


Average depreciation


of free-floating exchange rate regime and increase in trade to GDP ratio.

1.3 Asymmetry and Non-linearity

Pass-through can differ between depreciation and appreciation (asymmetry), and between large and small change (non-linearity). When firms face capacity constraints and/or there are trade restrictions, pass-through is higher for depreciation than apprecia

tion [Knetter 1994; Pollard and Coughlin 2004].

Table 2: Model Estimates and Robustness Tests-1990:2 to 2005:3

Model Constant ΔP*t ΔPt-1 Fshockt ΔM t-1

Δet ΔYt

Model a 0.0037 0.373

0.069 0.052

(10.4) (5.4) (2.3)

(5.0) Model 0.0023 0.46 0.254

b 0.068 0.044

(4.9) (5.2) (6.7) (2.1) (4.5)
Model c 0.0022 0.057 0.39 0.042 0.30 0.14
(5.3) (4.9) (6.3) (2.2) (5.9) (6.8)
Model d 0.001 0.056 0.40 0.037 0.31 0.13 0.088
(1.4) (4.8) (6.5) (1.9) (6.1) (6.1) (1.9)

The figures in the parentheses are t-statistics; The reported statistics on LM test for serial correlation is f-statistics.

When firms are building up market share, appreciation allows firms to lower import prices even while maintaining their mark up, while depreciation leads to reduction in mark-up to keep price unchanged to maintain market share [Knetter 1994].

The non-linearity in pass-through arises in the presence of the menu cost and depends on the type of price invoicing. Under PCP, a small changes in the exchange rate are passed-though, but a large changes are absorbed by altering the invoice price, while the opposite happens with LCP [Pollard and Coughlin 2004].

Many empirical studies support asymmetry in pass-through, but the directions have varied. For the US, Mann (1986) found higher pass-through during appreciation than depreciation. For seven Asian countries, Webber (2000) finds the opposite to hold. With regard to non-linear response, Ohno (1989) finds Japanese

Figure 4: Rolling Regressions Coefficients

0.17 Short-run 0.24 Long-run
0.13 0.19
0.09 0.14
0.01 -0.01





remain unchanged for individual components. Fifth, trade distortions resulting from tariffs and quantitative restrictions by acting as a barrier to arbitrage of goods between countries would lead to lower pass-through. Sixth, in the presence of asymmetry and non-linearity, the pass-through would depend upon the period of appreciation and depreciation and the size of exchange rate change during various sub-periods.

2 Data Issues and Stylised Facts

This section discusses the data issues and stylised facts.




2.1 Source of Data

0.52 We use the monthly data during the period 1990:1 to 2005:3


0.62 0.09

0.62 0.02

from the Handbook of Statistics on Indian Economy (Reserve Bank of India). The variables are: wholesale price index (P)2, nominal effective exchange rate (e) defined as domestic currency per unit of foreign currency, index of industrial production (Y), broad money (M), and trade weighted foreign prices (P*). Trade weighted foreign prices is derived using the definition of real effective exchange rate adopted by RBI. As the real effective exchange rate (rer) is defined as weighted average of nominal effective exchange rate (e) × [wholesale price inflation (P) ÷ foreign inflation (P*)], we can derive P*=(e × P) ÷ rer.3 All the series are seasonally adjusted.

2.2 Some Stylised Facts

The annualised month-to-month average inflation rate, exchange rate change and their volatility for sub-sample period of five years in Table 1 (p 72) shows decline in average inflation and its volatility, particularly the former. The average depreciation rate also declined considerably due to increasing two way movements in the more recent times. On the other hand, the decline in volatility was far less prominent, particularly with the exclu

sion of depreciation in July 1991.

The rolling five years average in Figure 1 (p 72)

show that the annualised average month-to-month

inflation declined from over 10 per cent to around 4

to 5 per cent. Volatility also declined but to much

lesser extent.

Similarly, the average rate of depreciation steadily

declined due to increasing two way movements, re



2/99 2/95

export prices to respond more to large exchange rate changes than small changes. For 30 US import industries, Pollard and Coughlin (2004) also find most firms responding positively to the size of exchange rate change.

1.4 Factors Explaining Pass-Through

Thus, several factors affecting exchange rate pass-through can be identified: first, higher inflation and its volatility would lead to higher pass-through and vice versa; second, the impact of exchange rate volatility is not unambiguous, though some of the studies find that the higher the misalignment of RER higher is the pass-through; third, a higher import penetration ratio and higher imports and exports to GDP ratio lead to higher pass-through; fourth, the composition of imports with varying degrees of pass-through affects aggregate pass-through even when they

Economic & Political Weekly EPW April 19, 2008



sulting in appreciation in the more recent period

(Figure 2, p 72). The volatility, excluding the major devaluations in July 1991, on the other hand, appears to have not changed much.

3 Empirical Framework

We discuss here the model used in the exercise.

3.1 Model Estimated

Drawing on the literature [Bailliu and Fujii 2004], a reduced form specification is derived from the profit maximising behaviour of an exporting foreign firm of the following type, Maxπ = e–1PQ – C(Q) ...(1)


where ‘π’ is profit in exporting firm’s currency, ‘e’ is the exchange rate of domestic currency per exporting firms currency, ‘P’ is price in domestic currency, C(Q) is the cost function in exporting

SPECIAL ARTICLEapril 19, 2008 EPW Economic & Political Weekly74firm’s currency and ‘Q’ is the quantity demanded. The first order condition for maximisation of (1) is derived as,P = eCq μ ...(2)where ‘Cq’is the marginal cost and ‘μ’ is the mark-up over marginal cost which depends on the price elasticity of demand of the good. Thus, the price in domestic currency ‘P’ can change as a result of exchange rate, change in marginal cost of the firm and mark-up. The marginal cost will change because of local input cost, while the mark-up can change due to change in demand factors in the domes-tic country. Thus, in reduced form, the price equation is written as,Pt = α0 + α1 et + α2 P*t + α3 Yt + εt ...(3)where ‘P*’ is exporting firm’s marginal cost and ‘Y’ is domestic demand conditions, withα1 as the measure of pass-through. In the literature, variants of (3) are used to estimate pass-through [Golberg and Knetter 1996]. To estimate pass-through at the aggregate price level, the following issues needs to be taken into account, and accord-ingly adapt (3). As macroeconomic variables such as price, out-put and ex-change rate are generally as-sumed to follow a non-station-ary process I(1), the specifica-tions are com-monly used in first difference, i e, intheform of an inflation equation[Bailliu and Fujii 2004 among others].Inourcase,asthe unit root properties discussed in the Appendix (p 78) show that all the variables are stationary in firstdifference,andareinany casenotcointegrated in level form, we also consider the speci-fication in first difference in order avoid spurious relationship. Second, the lagged effects of the explanatory variables need to be taken into account, leading to an inflation equation of the type. n n * nΔPt = α0 + α1 ΣΔet–i + α2ΣΔPt–i + α3ΣΔYt–i + εt ...(4) i=0 i=0 i=0Third, (4) being an inflation equation, we account for inflation persistence by following an adaptive expectations approach andinclude lags of inflation. This also allows us to distinguish between short-and long-run pass-through. n n n * nΔPt = α0+α1ΣΔPt–i+α2ΣΔet–i + α3ΣΔPt–i + α4ΣΔYt–i ...(5) i=1 i=0 i=0 i=0Fourth, in India shock in primary commodities, particularly food prices, due to adverse supply conditions often affects the general price level. Following Mohanty and Klau (2001) food price shock ‘fshock’ is defined as the excess of current food price inflation over the general price inflation of the previous year, leading to the following specification. n n n * nΔPt = α0 + α1 ΣΔPt–i + α2ΣΔet–i + α3ΣΔPt–i + α4ΣΔYt–i i=1 i=0 i=0 i=0 n + α5Σ fshockt–i + εt ...(6)i=0Finally, as much of the monitoring of inflationary situation in India is done through the monitoring of growth of money supply, it is also included as an additional variable. Thus, the final aug-mented equation is of the following type.4 n n n * nΔPt = α0 + α1 ΣΔPt–i + α2ΣΔet–i + α3ΣΔPt–i + α4ΣΔYt–i i=1 i=0 i=0 i=0 n n + α5Σ fshockt–i + α6ΣΔMt–i + εt ...(7)i=0 i=0 where ‘M’ stands for money supply. The lagged inflation term gives the speed of pass-through to inflation. The short-run pass-through coefficient is given by α2 and the long-run coefficient by α2/(1 – α1 ). 3.2 Asymmetry and Non-linearityThe asymmetry and non-linearity is estimated by interaction of the exchange rate variable with appropriate dummies in the following manner.Asymmetry: Two dummies for appreciation and depreciation respectively are:DA = 1 for Δe < 0, 0 otherwise and DD = 1 for Δe > 0, 0 otherwiseInteraction of the above dummies with exchange rate change yields the equation n n n n *ΔPt = α0 +α1 ΣΔPt–i+α2A ΣDAΔet–i + α2DΣ DDΔet–i + α3ΣΔPt–i i=1 i=0 i=0 i=0 n n n + α4ΣΔYt–i + α5Σ fshockt–i + α6ΣΔMt–i + εt ...(8)i=0 i=0 i=0 withα2A andα2D as the pass-through coefficients for appreciation and depreciation, respectively.Non-linearity: The two dummies for absolute large and small change respectively, are:DL = 1 for Δe>threshold, 0 otherwise and DS = 1 for Δe < threshold, 0 otherwise Interaction of the above dummies with exchange rate change yields the equation, n n n n *ΔPt = α0 +α1 ΣΔPt–i+α2L ΣDLΔet–i + α2SΣDSΔet–i + α3ΣΔPt–i i=1 i=0 i=0 i=0 n n n + α4ΣΔYt–i + α5Σ fshockt–i + α6ΣΔMt–i + εt ...(9)i=0 i=0 i=0 withα2L andα2S as the pass-through coefficients for large and small changes, respectively.4 EmpiricalResultsThe following are the empirical results.4.1 RobustnessTests: Table 2 (p 73) presents the results ob-tained from the estimation of alternative specifications defined by (4) to (7) representing model A to model D, respectively.5,6 The model A is well estimated with all the variables statistically significant, has reasonable explanatory power, and does not suf-fer from serial correlation. There is substantial difference be-tween the coefficient of foreign price (input cost) and the ex-change rate. The exchange rate pass-through (0.07 per cent) is much lower than input cost pass-through (0.37 per cent), with Wald test [19.51(0.00)] decisively rejecting the equality between Table 3: Trend Fits on Rolling Regression CoefficientsPass-Through α1 α1 + α3 R-bar Wald Wald SquareTestTest α1=0 α1+α3=0Short-run 0.00023 0.23 37.0 (6.1) [0.00]Short-run 0.0008-0.00013 0.76 386 1.60 (19.6)(-1.3)[0.00][0.21]Long-run 0.0005 0.62201.0 (14.2) [0.00]Long-run* 0.00080.0013 0.75 236.0 50.0 (15.4)(7.1)[0.00][0.00]The figures in round brackets are t-statistics and those in square brackets are p-values; * Each of the slope coefficients in the two sample periods are greater than the average for the full period, which is accounted by decline in intercept dummy not reported.

the two. This can arise as foreign firms consider change in input cost to be more permanent that than exchange rate changes that more of the former is passed-through.

Figure 5: Rolling Regression – Asymmetry and Non-linerity







0.04 -0.012/1996 2/1998






0.01 -0.01 2/1996 2/1998 Appreciation Depreciation






0.01 -0.01

2/1996 2/1998 2/2000 2/2002 2/2004 2/2000 2/2002 2/2004

run and long-run pass-through coefficients ob-

Large Small

tained from rolling regressions, along with the 90


per cent confidence intervals.10 It can be seen that


the short-run pass-through coefficients rose from about 0.03 to about 0.11 up to mid-2001 and then


falls to about 0.07. The rise in the long-run pass


2/1996 2/1998 2/2000 2/2002 2/2004 through, on the other hand, is much more consist


2/2000 2/2002 2/2004


The inclusion of the autoregressive term (model B) does not alter the pass-through coefficient, though it can differentiate the short-run and long-run pass-through while the explanatory power improves. The alterations in the impact of foreign prices and the domestic demand shocks cannot be considered as fundamentally different. Further inclusion of food price shock (model C) leads to a slight decline in the pass-through coefficients (both the short and long-run), but is not substantial and fundamentally different. The explanatory power improves markedly. Augmenting with change in money supply (model C) hardly makes any difference in terms of the coefficients and the explanatory power compared to model C. Thus, the estimated pass-through coefficients are robust to alternative specifications incorporating important determinants of inflation in India. In the remaining, we analyse pass-through using model C, as we essentially estimate an augmented supply curve and therefore, as mentioned above, including money supply may not be appropriate.

4.2 Comparison of Coefficients with Earlier Estimates: Estimated pass-through coefficients of 0.06 in the short-run and 0.08 to 0.09 in the long-run imply 10 per cent change in exchange rate, and lead to increase in final prices by 0.6 to 0.9 per cent. Such magnitudes of pass-through to final prices are typically estimated and are similar to the estimates of Choudhri and Hakura (2001) of

0.06 and 0.10, respectively for India. The short-run pass-through is larger than the average pass-through of low inflation countries and several industrialised countries, while the long-run pass-through is somewhat lower than the average reported by them on quarterly data for 1979 to 2000. Devereux and Yetman (2003) using annual data during 1970 to 2001, however, estimate a much higher passthrough of 0.36 for India, as inflation gets accumulated over a year while exchange rate change may not be large due to both way movements.

4.3 Stability of Coefficients:The stability of the coefficients using the parameter stability test of Hansen (1991) finds the coefficients to be stable.7 Andrews and Ploberger (1994) test also reveals no structural break in the individual coefficients and jointly.8 The recursive estimates of the coefficients, however, show an overall

rise in the coefficient of the exchange rate (Figure 3, p 72). Thus, the pass-through coefficient could have undergone a gradual change, which is not captured by the above tests. Thus, we carry out rolling regressions.

4.4 Pass-Through Coefficients from Rolling Regressions9: Figure 4 (p 73) shows the short

ent and steady, increasing from about 0.04 to

more than 0.13.

Two trends were fitted to observe the increase: (1) PT = β0 + β1Trend, where PT is the series of pass-through coefficients obtained from the rolling regressions. For β1> 0 pass-though has increased, β1 < 0 the pass-through has declined and β1 = 0 there is no change. (2) PT = β0 + (β2 + β0) Dummy + β1 Trend + (β1 + β3)Dummy*Trend. Dummy takes the value of 1 from the point of significant trend break and thereafter, and 0 otherwise.11 The selection criterion is the highest R-bar square. β1 is the trend before the identified pointand thereafter, it is (β1 +β3).

Table 3 (p 74) shows that both the short-run and long-run passthrough increased.12 While the short-run coefficient increased by a monthly average of 0.00023, the long-run coefficient increased by a higher monthly average of 0.0005. The Wald tests indicate that the increases are significantly different from zero. For the short-run coefficient, after increasing by a monthly average of 0.0008, it has levelled off (the Wald test rejects the decline by -0.00013). On other hand, the increase in long-run coefficients accelerates from a monthly average increase of 0.0008 to a monthly average of 0.0013 (the Wald test shows statistical significance).

Figure 6: Openness and Import Penetration Ratio


30 Openness

20 Import penetration


0 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004

The positive slope in the trend of rolling regression co efficients, however, does not ensure that the coefficients are statistically different from each other. Therefore, we perform Wald-test between the coefficients of six pairs of windows, viz: the first and the 5th window (with lowest short-run and long-run coefficient) against each of the windows with highest short-run coefficient

Economic & Political Weekly EPW April 19, 2008

20 40 60


1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003

0 92-9 2 3
SPECIAL ARTICLEEconomic & Political Weekly EPW April 19, 200879policy on inflation control. This under-scores the need to control fiscal imbalances of government. In any case, a greater mon-etary autonomy, and therefore, credible monetary policy is achieved with a prudent fiscal policy, and not with fiscal profligacy.Notes 1 On the contrary, Otani et al (2003) in the case of Japan finds that the decline in the exchange rate pass-through to import prices came mainly from declines in each product, rather than a shift in composition of imports. Marazzi et al (2005) find that shift in the composition of core imports pro-vides only a partial explanation for decline in the aggregate pass-through to US import prices. 2 WPI is considered as it is the headline measure of inflation computed on all-India basis with larger coverage of commodities, released at higher fre-quency with lesser lag that coincides with the release of monetary data and is more easily un-derstood by the public.3 Effective exchange rates based on 36-countries bilateral trade weights is considered as it more comprehensive in terms of coverage. 4 As the final specification is of a back-ward-looking augmented Phillips curve type, including money supply variable may not be appropriate. However, it has been retained to test for robustness of the estimated pass-through coefficient among the alternative models. 5 Dummy variables were used to control for few in-stances of month-to-month rate of domestic and foreign inflation, which on an annualised basis were over 18 per cent. Month-to-month inflation series is generally volatile due to measurement error or temporary factors unrelated to underly-ing inflation trends, which is controlled by the included dummies. 6 The lag lengths were selected based on their statistical significance. Starting from the maximum of 11 lags, as they are monthly data, statistically in-significant lags were progressively dropped.7 The test statistics for Δe, ΔPt-1 and joint stati-stics are 0.19, 0.22 and 1.2, which is less than 5 per cent critical values of 0.47, 0.47 and 1.2, respectively. 8 The Andrews-Ploberger LM test statistics for Δe, ΔPt-1 and all coefficients were 0.28, 0.99 and 4.73 with p-value of 0.67, 0.20 and 0.52, respectively. 9 The reported results are for model C for five years window size. Similar results are obtained for window sizes of six and seven years and for other models with different window sizes. They are not reported due to space constraints but are avail-able from the author. 10 The standard error of the long-term coefficients to derive the confidence interval is estimated as, 1 2 α2 2 se=√( ) Variance[α2] + ( ) Variance[α1] (1–α1) (1–α2)2 1 α2 + 2 ( )( ) Covariance(α1, α2). (1–α1) (1–α2)2 11 Since this point is not known a priori, we search it within a range of 15 per cent to 85 per cent of the sample period, which is the standard practice in the literature to locate structural breaks at an unknown point of time.12 The increase is indicated in all the window sizes and for the alternative specifications, which are not reported due to space constraints, but are available from the author.13 Wald test [0.51(0.48)], however, does not reject the equality between the coefficients, and therefore, the evidence of presence of asymmetry is rather weak.14 As rolling at both ends gave highly volatile coef-ficients, we fixed the starting date at 1996:2 and kept adding a new observation up to the full sample period, i e, roll at one end only. 15These are non-annualised month-to-month absolute changes.16 The Wald test [3.88 (0.05)] rejects the equality of the coefficients at 5 per cent level with threshold of 2 per cent. Therefore, the evidence on non-line-arity is much stronger than that of asymmetry.17 The reported rolling regressions are with sample average as the threshold level.18 It is called conjectural as direct tests were not pos-sible due to non-availability of monthly data on most macroeconomic variables. Thus, using annual data and supported by theoretical and empirical evidences in literature, the inferences were drawn. 19 India with 3.1 per cent of global oil consump-tion was the sixth largest consumer of petroleum products in 2003, up from 2.2 per cent and 14th place in 1993 [Pattnaik and Samantaraya 2005].20 The current account balance, however, has reversed its trend in the most recent period.ReferencesAhluwalia, Montek S (2002): ‘Economic Reforms in India since 1991: Has Gradualism Worked?’, Journal of Economic Perspectives, Vol 16, pp 67-88.Andrews, Donald W K and Werner Ploberger (1994): ‘Optimal Tests When a Nuisance Parameter Is Present Only under the Alternative’, Econo-metrica, Vol 62, No 6, pp 1383-1414.Bacchetta, Philippe and Eric vanWincoop (2001): ‘A Theory of the Currency Denomination of Inter-national Trade’, DNB Staff Reports No 75.Bailliu, Jeannine and Eiji Fujii (2004): ‘Exchange Rate Pass-Through and the Inflation Environment in Industrialised Countries: An Empirical Investiga-tion’, Bank of Canada Working Paper N0 2004-21, Bank of Canada, Ottawa.Belaisch, Agnes (2003): ‘Exchange Rate Pass-Through in Brazil’, IMF Working Paper No 03/141, Inter-national Monetary Fund, Washington.Betts, C and M Devereux (1996): ‘The Exchange Rate in a Model of Pricing-to-Market’,European Eco-nomic Review, 40, pp 1007-21. – (2000): ‘Exchange Rate Dynamics in a Model of Pricing-to-Market’, Journal of International Eco-nomics, 50(1), pp 215-44.Bhundia, Ashok (2002): ‘An Empirical Investigation of Exchange Rate Pass-Through in South Africa’, IMF Working Paper No 02/165, International Monetary Fund, Washington.Campa, Jose Manuel and Linda S Goldberg (2004): ‘Exchange Rate Pass-Through into Import Prices’, CEPR Discussion Paper Series No 4391, Centre for Economic Policy Research, London.Cecchetti, Stephen and Guy Debelle (2004): ‘Has the Inflation Process Changed?’, paper prepared for the Third BIS Annual Conference ‘Understanding Low Inflation and Deflation’ Brunnen, Switzer-land, June 18-19.Choudhri, U Eshan and Dalia S Hakura (2001): ‘Exchange Rate Pass-Through to Domestic Prices: Does the Inflationary Environment Matter?’, IMF Working Paper No 01/194 International Monetary Fund, Washington.Devereux, M B and J Yetman (2003): ‘Price-setting and Exchange Rate Pass-Through: Theory and Evidence’ inPrice Adjustment and Monetary Policy, proceedings of a conference held by the Bank of Canada, Ottawa, November 2002, pp 347-71. Dornbusch, R (1987): ‘Exchange Rates and Prices’, American Economic Review, Vol 77,pp93-106.Engel, C (2002): ‘The Responsiveness of Consumer Prices to Exchange Rates: A Synthesis of Some New Open Economy Macro Models’, The Manchester School, 70, pp 1-15.Engle, R and C Granger (1987): ‘Cointegration and Error Correction: Representation, Estimation and Testing’, Econometrica, 55, pp 251-76.Frankel, Jeffrey, David Parsley and Shang-Jin Wei (2005): ‘Slow Pass-Through around the World: A New Import for Developing Countries’, NBER Working Paper 11199.Gagnon, J E and Jane Ihrig (2004): ‘Monetary Policy and Exchange Rate Pass-Through’, Board of Governors of the Federal Reserve System, Inter-national Finance Discussion Paper No 704.Goldberg, K Pinelopi and Michael M Knetter (1996): ‘Goods Prices and Exchange Rates: What Have We Learned?’, NBER Working Paper 5862.Goldfajn, Ilan and Sergio Riberio da Costa Werlang (2000): ‘The Pass-Through from Depreciation to Inflation: A Panel Study’, Banco Central do Brasil Working Paper Series No 5, Brasilia.Gregory, Allan W and Hansen Bruce E (1996): ‘Resid-ual Based Tests for Cointegration in Models with Regime Shifts’,Journal of Econometrics, 70(1), pp 99-126. Hansen (1991): ‘Parameter Instability in Linear Models’, Journal of Policy Modelling, 14 (4), pp 517-33.Kang, Sammo and Yunjong Wang (2003): ‘Fear of Inflation: Exchange Rate Pass-Through in East Asia’, KIEP Working Paper 03-06, Korea Institute for International Economic Policy, Seoul.Knetter, Michael M (1994): ‘Is Export Price Adjustment Asymmetric? Evaluating the Market Share and Marketing Bottlenecks Hypotheses’,Journal of International Money and Finance, 13 (1), pp 55-70.Krugman, P (1987): ‘Pricing to Market When the Ex-change Rate Changes’ in S Arndt and J Richardson (eds),Real-Financial Linkages among Open Econo-mies, MIT Press, Cambridge, Massachusetts.Leigh, Daniel and Marco Rossi (2002): ‘Exchange RatePass-Through in Turkey’, IMF Working Paper No 02/204, International Monetary Fund, Washington.Mann, Catherine L (1986): ‘Prices, Profit Margins, and Exchange Rates’,Federal Reserve Bulletin, 72(6), pp 366-79.Marazzi, M, Nathan Sheets, Robert Vigfusson and Others (2005): ‘Exchange Rate Pass-Through to US Import Prices: Some New Evidence’, Board of Governors of the Federal Reserve System, Inter-national Finance Discussion Paper No 833.McCarthy, Jonathan (1999): ‘Pass-Through of Ex-change Rates and Import Prices to Domestic Inflation in Some Industrialised Economies’, BIS Working Paper No 79, Bank for International Settlements, Basel.Mohanty, M S and Marc Klau (2001): ‘What Determines Inflation in Emerging Market Economies’, BIS Papers No 8, Bank for International Settlements, Basel.Ohno, Kenichi (1989): ‘Export Pricing Behaviour of Manufacturing: A US-Japan Comparison’, IMF Staff Papers, 36(3), pp 550-79.O’Reilly, Gerard and Karl Whelan (2004): ‘Has Euro-Area Inflation Persistence Changed Over Time?’, Europe-an Central Bank Working Paper Series 335.Otani, Akira, Shigenori Shiratsuka and Toyoichiro Shirota (2003): ‘The Decline in the Exchange Rate Pass-Through: Evidence from Japanese Import Prices’,Monetary and Economic Studies, October, Institute for Monetary and Economic Studies, Bank of Japan, pp 53-81.Pattnaik, R K and Amaresh Samantaraya (2005): ‘The Evolving Inflation Process: Review of Indian Ex-perience’, paper presented in Autumn Economists’ Conference during October 27-28, 2005 at Bank for International Settlements, Basel. Phillips, P C B and P Perron (1988): ‘Testing for a Unit Root in Time Series Regression’,Biometrika, 75, pp 335-46.Pollard, Patricia S and Cletus C Coughlin (2004): ‘Size Matters: Asymmetric Exchange Rate Pass-Through at the Industry Level’, FRB Working Paper Series 2003-029C, The Federal Reserve Bank of St Louis.Reserve Bank of India (2001): ‘Currency-Wise Pattern of Invoicing of India’s Imports and Exports: 1990-91 to 1999-2000’, Reserve Bank of India Bulletin, April.Taylor, B John (2000): ‘Low Inflation, Pass-Through and the Pricing Power of Firms’, European Eco-nomic Review, 44 (7), pp 1389-1408.Webber, Anthony (2000): ‘Newton’s Gravity Law and Import Prices in the Asia Pacific’,Japan and the World Economy, 12(1), pp 71-87.

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