Exchange Rate Volatility and Exports: New Empirical Evidence from the Emerging East Asian Economies

Chit, Myint Moe; Rizov, Marian; Willenbockel, Dirk

doi:10.2139/ssrn.1157035

Cited by 40 publications

(53 citation statements)

References 57 publications

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“…() and Chit et al . (), the first‐difference of the log of monthly exchange rates is assumed to follow a random walk with a drift:

Δ e_{i j t}^{k} = {italicα}_{0}^{k} + {italicα}_{i j t}^{k} Δ e_{i j t - 1}^{k} + u_{i j t}^{k},

where u ijt ~ N (0, h ijt ) and

Δ e_{i j t}^{k}

denotes the first‐difference of the natural log of the bilateral RER of industry k at t period between countries i and j . The conditional variance is defined as:

h_{i j t}^{k} = {italicβ}_{0}^{k} + {italicβ}_{1}^{k} u_{i j t - 1}^{k, 2} + {italicβ}_{2}^{k} h_{i j t}^{k},

where

u_{i j t - 1}^{k, 2}

denotes the square of residuals,

u_{i j t - 1}^{k}

, estimated by the ARCH model at t − 1 period.…”

Section: Methodsmentioning

confidence: 99%

“…Recent empirical studies, however, have found that the exchange rate volatility has significantly negative effect on intra‐Asian trade (e.g. Thorbecke, ; Hayakawa and Kimura, ; Chit et al ., ; and Tang, ). These studies focused on a particular industry (electronic components in Thorbecke, ), and the difference between final and intermediate goods (Hayakawa and Kimura, ; and Tang, ).…”

Section: Introductionmentioning

confidence: 96%

See 1 more Smart Citation

Industry‐specific exchange rate volatility and intermediate goods trade in Asia

Sato

Shimizu

Shrestha

et al. 2016

Scottish J Political Eco

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This paper empirically analyzes the effect of exchange rate volatility on intra-Asian trade of intermediate goods at an industry level by constructing a new dataset of the industry-specific bilateral real exchange rate. As the final processed exports are destined for countries outside the Asian region, both the exchange rate and world demand are considered as a possible driving force in the cross-border fragmentation and processing trade. It is found that, in contrast to the recent studies, the exchange rate impact on intra-regional trade differs across industries. The exchange rate volatility has negative and significant effects only on the general machinery industry and a part of the electric machinery industry with more differentiated products, even when taking into account the world's demand for the final processed exports. These findings are supported by various kinds of exchange rate volatility in the short-and long-run. Our empirical results suggest that the different impact of the exchange rate volatility across industries is tied to the characteristics of traded goods in respective industries.

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“…() and Chit et al . (), the first‐difference of the log of monthly exchange rates is assumed to follow a random walk with a drift:

Δ e_{i j t}^{k} = {italicα}_{0}^{k} + {italicα}_{i j t}^{k} Δ e_{i j t - 1}^{k} + u_{i j t}^{k},

where u ijt ~ N (0, h ijt ) and

Δ e_{i j t}^{k}

denotes the first‐difference of the natural log of the bilateral RER of industry k at t period between countries i and j . The conditional variance is defined as:

h_{i j t}^{k} = {italicβ}_{0}^{k} + {italicβ}_{1}^{k} u_{i j t - 1}^{k, 2} + {italicβ}_{2}^{k} h_{i j t}^{k},

where

u_{i j t - 1}^{k, 2}

denotes the square of residuals,

u_{i j t - 1}^{k}

, estimated by the ARCH model at t − 1 period.…”

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 96%

Industry‐specific exchange rate volatility and intermediate goods trade in Asia

Sato

Shimizu

Shrestha

et al. 2016

Scottish J Political Eco

View full text Add to dashboard Cite

show abstract

“…The key explanatory variable in regression (3) is the firm‐level exchange rate risk,

E R R_{italickt}

. Following Chit, Rizov, and Willenbockel (), we first define a proxy for exchange rate volatility,

V_{jt}

, for country j in year t :

V_{italicjt} = \sqrt{\sum_{m = 0}^{11} \frac{{false(normalΔ \ln (R E R_{j t, (- m - 1, - m)}) - \bar{normalΔ \ln false(R E R_{j t, false(- m - 1, - m false)} false)} false)}^{2}}{11}}

Here,

Δ \ln (R E R_{j t, (- m - 1, - m)})

is the first difference of the log monthly exchange rate in year t and m represents the month. Thus, in each year t , we have 12

Δ \ln (R E R_{j t, (- m - 1, - m)})

s.…”

Section: Exchange Rate Risk and Trade Mode Choicementioning

confidence: 99%

Exchange rate risk and trade mode choice in processing trade: Evidence from Chinese data

Chen

Jiang

Sun

2019

Rev International Economics

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This study investigates the impact of exchange rate fluctuations on the trade mode choices of assembly firms. Using Chinese customs data, we show that exchange rate pass‐through (ERPT) depends on which party is responsible for sourcing inputs. Relative to passively receiving inputs under the pure assembly (PA) mode, foreign‐invested assembly firms mainly source inputs themselves through the import and assembly mode and enjoy lower ERPT. We find that the share of imports through PA increases with exchange rate fluctuations. This effect is more pronounced for firms in liquidity‐constrained industries and mitigated by better local financial development.

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“…In some recent studies, the gravity model is used to analyze the effects of exchange rate volatility, trade liberalization, and regional integration on East Asian trade flows (Chit et al . ; Jongwanich ; Sheng et al . ).…”

Section: Analytical Framework and Datamentioning

confidence: 99%

“…Chit et al . ) suggests estimation of the gravity model using fixed effects (FE) may not be reliable because of potential endogeneity. There has been a growing trend to estimate the dynamic panel using the instrumental variable (IV) or the generalized method of moments (GMM) techniques to address endogeneity.…”

Section: Analytical Framework and Datamentioning

confidence: 99%

Global Financial Crisis and Southeast Asian Trade Performance: Empirical Evidence

Kabir

Bloch

Salim

2018

Rev Urban & Reg Develop

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The literature on the recent Global Financial Crisis (GFC) focuses on the decimation of Western economies; however, the impact of the crisis on Asian economies has remained largely unexplored. Using the classic dependency approach of the “core‐periphery” framework, this paper investigates the trade performance of Association of South East Asian Nation (ASEAN) members during (2008–2009) and after (2010–2012) the GFC and analyses the transmission of shocks to these countries from the Western core. A modified gravity model of trade flows is estimated for a panel of five leading ASEAN economies and their trading partners for the period 2002–2012. The empirical results show a decline in ASEAN trade during the financial crisis that becomes stronger during the post‐crisis period. The decline in trade exceeds that associated with changing gross domestic product at home and abroad, suggesting the crisis and its aftermath have been particularly disadvantageous for ASEAN trade.

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Exchange Rate Volatility and Exports: New Empirical Evidence from the Emerging East Asian Economies

Cited by 40 publications

References 57 publications

Industry‐specific exchange rate volatility and intermediate goods trade in Asia

Industry‐specific exchange rate volatility and intermediate goods trade in Asia

Exchange rate risk and trade mode choice in processing trade: Evidence from Chinese data

Global Financial Crisis and Southeast Asian Trade Performance: Empirical Evidence

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