Exchange rate Pass-through

The baseline equation to estimate the exchange rate pass-through follows the work of Campa and Goldberg (2005):

∆p = α + ∑ a ∆e + ∑ b ∆w + c ∆y + ϵ (4.1) where p denotes import prices of a specific industrial sector for country j at time t, e presents the nominal effective exchange rate (domestic currency per unit foreign currency), w presents a primary control variable reflecting exporters costs, and y captures destination market demand condition. All variables are expressed in logarithm and in their first differences. To take the gradual adjustment of import prices to exchange rate changes into accounts, the variables of exchange rates and exporter production cost are structured into the regression up

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to their fourth lags. The clarification of four lags as long run is empirically certified as pass- through rates generally respond over the first and second lags after an exchange rate adjustment. The import prices generally respond to exchange rates’ changes up to the second lag, thus four lags are validated to describe the long run effects of exchange rates’ changes, as most of past literature verified.

The underlying micro foundation of this regression can be expressed as:

p = ϕ + (1 + ϕ )e + c y + c w (4.2) where p denotes import prices and w denotes the changing costs in the exporting countries. This structure gives the exchange rate pass-through β = 1 + ϕ . If β = 1, then producer currency pricing (PCP) takes place in the international market; if β = 0 , then local currency pricing (LCP) takes place. Various empirical work shows that the exchange rate pass-through is neither pure PCP nor LCP. When e increases, local currency depreciates, therefore the import prices are expected to increase in this case. This indicates import prices and exchange rate are supposed to be positively related. In addition, this allows the exchange rate pass- through to rely on the market structure, which consists with the previous theoretical and empirically literature stating that exchange rate pass-through rates are affected by the market structure, such as Dornbusch (1987) and Marston (1990), and empirically supported by Knetter (1992) and Yang (1997).

The short run exchange rate elasticity on import prices is estimated by a , while the long run relationship between exchange rates and the import prices is measured by ∑ a , the sum of the current and four lags of exchange rates’ coefficients. The clarification of four lags as long run is empirically certified as pass-through rates generally respond over the first and second lags after an exchange rate adjustment. The foreign production cost is measured by a constructed proxy which tends to model the changing costs of a country’s aggregated trading partners, expressed as:

W = REX ∗ P /NEX ,

101 w = rex + p − nex .

The aim of this measure is to present a comprehensive weighted cost of country j’s trading partners, with each partner weighted by its trading importance to the importing country. The trading importance of each partner to the importing country is reflected by the effective exchange rate of the importing country. This variable w is interpreted as the comprehensive wage of all exporting countries for country j. The destination market demand conditions y is explored by five measurements: GDP, GDP growth rate, IMP, IMP growth rate, BCI_Euro, BCI_UK.

Table 40 : Variables Definition

Variable Definition

p Import prices of a specific industrial sector for country j in period t

e Nominal effective exchange rate in log (domestic currency per unit foreign currency)

NEX Nominal effective exchange rate (domestic currency per unit foreign currency)

REX Real effective exchange rate (domestic currency per unit foreign currency)

w Primary control variable reflecting exporters costs

y Destination market demand condition

z Tested determinants of exchange rate pass-through

The table summarizes the definition of each variable used.

4.2.1.1. Negative and Positive BCIs

Dummy variables are also adopted to test effects of the negative and positive Business Climate Index (BCI_Euro, BCI_UK) on the import prices changes by using the following equation: ∆p = α + ∑ a ∆e + ∑ b ∆w + c( )_BCI( )_{+ c}( )_BCI( )_{+ ϵ (4.3)}

4.2.1.2. Macroeconomic Environment Cost and Industry-specific Cost

Exchange rate pass-through is closely related to the costs in production and trading strategies behind international trades, therefore, here two different production cost measures are

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constructed to depict exporters’ behaviours. In the market, producers can choose to adjust their product prices to the general macroeconomic environment to meet their own conditions, or to the industry-specific shocks that will impacts on the production. The generalization of those two indicators comes from the idea to test how exchange rate pass-through will respond to the different situations where macro environment shock is more dominant over the industry, or the industry shock is more dominant over the macro environment in terms of production cost. Since producers need to cooperate with shocks occurred both in the general market and in its specific industry, while those shocks are not necessarily spontaneous or at the same level. It is hypothesized that an exporter will choose to adjust their prices along with the general macroeconomic environments if the exporter is less competitive in this industry. Similarly, an exporter will choose to adjust their prices along with the general industry condition if the exporter is more competitive in this industry. This is under the assumption that the shocks in the specific industry will not have strong influences on macroeconomic environment.

When general macroeconomic environment is more dominant in exporting producers’ cost than the industry condition, in other words, when the exporter is less competitive in the industry, the following cost variable is employed:

W = REX ∗ P( )/NEX

w = rex + p − nex Following Regression will be tested:

∆p = α + ∑ a ∆e + ∑ b ∆w + c ∆y + ϵ (4.4)

When the specific industry production condition is more dominant in the production condition than the general macroeconomic environment for exporting producers, that is, when the exporter is more competitive in the industry, the following cost variable is employed:

W = REX ∗ P /NEX w = rex + p − nex

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where P is the corresponding industry import prices, which is the same as the dependent variable on the left side of the equation. Regression (4.1) will be tested.

4.2.1.3. Robustness Check for Exchange Rate Pass-through

Considering the resilience and sluggishness as the features of price response, and the how variable w is constructed, the following regression equation can be used to compare the results as a robustness check by taking out the contemporaneous foreign production cost variable w of baseline Equation (4.1):

∆p = α + ∑ a ∆e + ∑ b ∆w + c ∆y + ϵ (4.5) ˙