# Lingfei Lu's MPhil Thesis Project

## 2021/09/17

**Keywords**: export variety choice, exchange rate shock, heterogeneous firms, multi-unit firm, firm boundaries, Chinese exporters

## 2021/09/24

- Question 1: What determines firms’ **export variety choice** in trade?
- Question 2: How will **exchange rate shocks** affect the firm’s decision?
- Question 3: What is the role of firm **size or units** in **heterogeneous responses** to shocks?

## 2021/09/28

- Kim, J. (2020). The Impact of Uncertainty Shocks on the Investment of Small and Large Firms: Micro Evidence and Macro Implications.
- Large firms show less investment decline in times of high uncertainty compared with small firms.
- The size effect arises from the fact that large firms operate in multiple production units but small firms operate in a single unit.
- With unit-level real and firm-level financial frictions, a multi-unit firm can utilize internal funds to relax financial constraints and thus dampen the real option effect due to uncertainty shocks.
- Fung, L., Baggs, J., & Beaulieu, E. (2011). Plant scale and exchange‐rate‐induced productivity growth. Journal of Economics & Management Strategy, 20(4), 1197-1230.
- A real appreciation of the domestic currency reduces shipments and this negative effect is larger for exporters.
- The appreciation-induced reduction of scale negatively affects productivity at the plant level. This scale effect more than offsets any potential gains from the appreciation-induced reduction in the price of imported inputs.
- Berman, N., Martin, P., & Mayer, T. (2012). How do different exporters react to exchange rate changes? Quarterly Journal of Economics, 127(1), 437–492.
- High–performance firms react to a depreciation by increasing significantly more their markup and by increasing less their export volume.
- This heterogeneity in pricing-to-market is consistent with models where the demand elasticity decreases with firm performance.
- Since aggregate exports are concentrated on high-productivity firms, heterogeneous pricing-to-market may partly explain the weak impact of exchange rate movements on aggregate exports.
- Tang, H., & Zhang, Y. (2012). Exchange rates and the margins of trade: Evidence from Chinese exporters. CESifo Economic Studies, 58(4), 671-702.
- We find significant effects on the extensive margin. A 10% real appreciation of the renminbi is associated with a 1 percentage point decline in the probability of entry, and a 0.2 percentage point increase in the probability of exit.
- The effects among foreign-invested enterprises almost double for both entry and exit.
- The response to exchange rate shocks is relatively fast: The exchange-rate elasticity of exports is estimated to be around 0.4 in the first year after the shock, with most of the adjustment taking place in the first six months, probably due to intense competition in the Chinese export sectors.
- Chatterjee, A., Dix-Carneiro, R., & Vichyanond, J. (2013). Multi-product firms and exchange rate fluctuations. American Economic Journal: Economic Policy, 5(2), 77-110.
- In response to a real exchange rate depreciation, firms increase markups for all products, but markup increases decline with firm-product-specific marginal costs of production.
- In response to an exchange rate depreciation, producer price increases are more pronounced for products closer to the core competency.
- Mayer, T., Melitz, M. J., & Ottaviano, G. I. P. (2014). Market Size, Competition, and the Product Mix of Exporters. American Economic Review, 104(2), 495–536.
- They incorporate a linear demand system in their framework to allow for the endogeneity of markups.
- Tougher competition in an export market induces a firm to skew its export sales toward its best-performing products.
- The within-firm change in product mix driven by the trading environment has potentially quite large effects on firm productivity.

- Li, H., Ma, H., & Xu, Y. (2015). How do exchange rate movements affect Chinese exports? - A firm-level investigation. Journal of International Economics, 97(1), 148–161.
- RMB price response to exchange rate changes is very small, indicating relatively high exchange rate pass-through into foreign currency denominated prices, while the volume response is moderate and significant.
- Exporters with higher productivity price more to market, though the pass-through is still very high.
- RMB appreciation reduces the probability of entry and the probability of continuing in the effort market.
- Héricourt, J., & Poncet, S. (2015). Exchange rate volatility, financial constraints, and trade: empirical evidence from Chinese firms. The World Bank Economic Review, 29(3), 550-578.
- Firms' decision to begin exporting and the exported value decrease for destinations with a higher exchange rate volatility and that this effect is magnified for financially vulnerable firms.
- Financial development seems to dampen this negative impact, especially on the intensive margin of export, since the existence of well-developed financial markets allows firms to hedge exchange rate risk.
- Xu, J., Mao, Q., & Tong, J. (2016). The impact of exchange rate movements on multi-product firms’ export performance: Evidence from China. China Economic Review, 39, 46–62.
- Use China's firm-level microdata and customs data over 2000–2007.
- A real appreciation of RMB narrows multi-product firms' export scope and induces firms to skew their export sales towards the best performing products.
- A real appreciation of RMB lengthens the export duration of core products but shortens the export duration of non-core products.

## 2021/10/08

For Xu, Mao, and Tong (2016), one innovation is using the interaction term between real effective exchange rate and firm TFP/product ranking to test heterogeneous impacts of exchange rate shocks.

For firm-level real effective exchange rates, they use 23 kinds of currencies of China's 34 largest trading partners. For other export destinations, they use the real exchange rate index of RMB against USD as an alternative measure.

For TFP estimation, they use the augmented Olley and Pakes (1996)'s method. For product ranking, they sort all the products according to their export sales within a given firm–destination–year triplet.

For export scope and skewness, they give a possible explanation that the bottom or marginal product is the fringe product that can bring positive profit to firms and will be abandoned faced with RMB exchange rate appreciation. This could be improved by an export choice model of multi-product firms.

Another innovation is using survival analysis to study the impact of exchange rate movements on firms' export duration. Specifically, they use Kaplan–Meier estimated survival function and the complementary log-log model.

## 2021/10/12

Amiti, Itskhoki, and Konings (2014) explain the variation of exchange rate pass-through across exporters by marginal cost and markup channels. They utilize import intensity proxying for marginal cost sensitivity to exchange rate and destination-specific market shares proxying for markup elasticity. They are positively correlated in the cross-section and together constitute a sufficient statistic for exchange rate pass-through.

In the theoretical part, the import intensity and export market shares are both endogenously determined. They use the Atkeson and Burstein (2008) oligopolistic competition model of variable markups and the Halpern, Koren, and Szeidl (2011) model of the firm’s choice to import intermediate inputs at a fixed cost.

They find that more import-intensive exporters have significantly lower exchange rate pass-through, as 1) they face offsetting import effects on marginal costs and 2) also have high export market shares and hence set high markups and actively move prices in response to changes in marginal cost.

They argue that this relationship holds independently of the general equilibrium environment and the coefficients could be estimated using cross-sectional variation without relying on strong partial equilibrium or exchange rate exogeneity assumptions.

We may improve this study by relaxing some assumptions. First, this paper does not consider endogenous exporting decisions about entry, exit, multi-destination, or multi-product. One reason for keeping the main product is that the import intensity and marginal cost measures may be different for all products produced by multiproduct firms. This may matter more for Chinese exporters if import-induced export is significant.

The second is about flexible price setting and currency choice. Price stickiness may happen when exporters are forced to fix their prices temporarily due to predetermined contracts or invoice currency. Strategic competition based on expectations of temporary shocks may also cause delayed pricing adjustments.

The final one is about real hedging. Although this paper argues that there is no evidence for firms choosing or switching import source countries to better hedge their export exchange rate risk, we could still study it based on either different measurements of hedging or different firm behaviors in Chinese firms.

## 2021/10/13

Meeting notes:

- Chinese firms have a diverse import pattern with active extensive margin adjustment
- Compare firms with multiple import sources vs single import source
- Incumbent vs new-entry exporters: more variation
- The difference in exchange rate pass-through from import variety

## 2021/10/20

Plan of tasks:

- Construct available customs datasets
- How long and frequent do we use it?
- Do we need the merged sample with CIE data?
- Shall we exclude non-importers from the sample?
- Summarize the overall import sourcing pattern of Chinese firms
- average number import sources
- firm dynamic about entry and exit
- Calculate firm-specific exchange rate pass-through for exporters
- Check whether exchange rate pass-through is correlated with import diversity
- control for firm size and import amount
- Find possible channels through which import diversity affects exchange rate pass-through
- endogenous choice of import sources
- interaction with firm export variety (inflow-outflow)

## 2021/11/10

Some quick ideas:

Chinese customs records use dollar-denominated value. Does this mean that Chinese export firms are more inclined to use Local Currency Pricing (for the US market) or Vehicle Currency Pricing (for other markets)?

Will a firm's pricing strategy be affected not only by country-specific but also firm-level exchange rate shocks?

## 2021/11/12

We first construct the log change in a firm f ’s export price of good I to destination country k at time t, follow Amiti, Itskhoki, and Konings (2014), with all prices are denoted by RMB.
$$
\Delta p_{EX;f,i,k,t} \equiv \Delta \log \left(\frac{\text {Export value}_{f, i, k, t}}{\text {Export quantity}_{f, i, k, t}}\right)
$$

$$
\Delta p_{IM;f, i, k, t} \equiv \Delta \log \left(\frac{\text {Import value}_{f, i, k, t}}{\text {Import quantity}_{f, i, k, t}}\right)
$$

The exchange rate shock is defined as the change of log price of foreign currency in terms of RMB, i.e. a positive shock means the foreign currency appreciates against RMB.

Then, I will try to run a simple reduced-form regression to calculate exchange rate passthrough, controlling for firm characteristics.
$$
\Delta p_{EX;f,i,k,t} = \alpha_{EX}\Delta e_{k,t}+\beta X_{f,t}+\epsilon_{f,i,k,t}
$$

$$
\Delta p_{IM;f,i,k,t} = \alpha_{IM}\Delta e_{k,t}+\beta X_{f,t}+\epsilon_{f,i,k,t}
$$

The results show weak coefficients for both export and import exchange rate pass-through.

## 2021/11/16

Heterogeneous exchange rate passthrough may come from two channels:

- Sourcing partners: building network, searching fixed cost, risk diversification & exposure
- Product scope: multiproduct exporters; core product choice; variable markup and marginal cost

Key literature about multiproduct firms:

- Chatterjee, A., Dix-Carneiro, R., & Vichyanond, J. (2013). Multi-product firms and exchange rate fluctuations. *American Economic Journal: Economic Policy*, *5*(2), 77-110.

- Chen, N., & Juvenal, L. (2016). Quality, trade, and exchange rate pass-through. Journal of International Economics, 100, 61–80.

We could plot exchange rate passthrough over time to find a macro trend in China and then discuss the mechanism.

e.g. Expanding firms will better absorb exchange rate shock consistent with the decreasing passthrough.

- Dong, Wei. 2012. “The role of expenditure switching in the global imbalance adjustment.” Journal of International Economics, 86(2): 237–251.

A generous reading about Exchange Rate: Charles Engel, "Chapter 8 - Exchange Rates and Interest Parity" in Handbook of International Economics, 2014

## 2021/11/30

The baseline empirical specification in BMM (2012):
$$
\ln \left(U V_{j i t}\right)= \alpha_{p} \ln \left(\widetilde{\varphi}_{j t-1}\right)+\beta_{p} \ln \left(R E R_{i t}\right)+\gamma_{p} \ln \left(\widetilde{\varphi}_{j t-1}\right) \times \ln \left(R E R_{i t}\right)+\psi_{t}+\mu_{j i}+\epsilon_{j i t}
$$
The empirical specification comparing the contribution of the within-sector and between-sector TFP variances in BMM (2012):
$$
\begin{aligned}
\ln \left(U V_{j i t}\right)= &\alpha_{p}^{W} \phi_{j t-1}^{W}+\alpha_{p}^{B} \phi_{s t-1}^{B}+\beta_{p} \ln \left(R E R_{i t}\right) +\gamma_{p}^{W} \phi_{j t-1}^{W} \times \ln \left(R E R_{i t}\right)\\
&+\gamma_{p}^{B} \phi_{s t-1}^{B} \times \ln \left(R E R_{i t}\right)+\psi_{t}+\mu_{j i}+\epsilon_{j i t}
\end{aligned}
$$
The baseline empirical specification in AIK (2014):
$$
\begin{aligned}
\Delta p_{f, i, k, t}^{*}=&\left[\alpha_{s, k}+\beta \varphi_{f, t-1}+\tilde{\gamma} S_{f, s, k, t-1}\right] \Delta e_{k, t} +\delta_{s, k}+b \varphi_{f, t-1}+c S_{f, s, k, t-1}+\tilde{u}_{f, i, k, t}
\end{aligned}
$$
The baseline empirical specification in Li, Ma and Xu (2015):
$$
\Delta \ln X_{f p c t}=\mu+\alpha_{X} \Delta \ln RER_{ct}+\beta_{X} \Delta \ln RGDP_{ct}+\xi_{fpc}+\tau_{t}+\varepsilon_{fpct}
$$
The empirical specification for firm heterogeneity and ERPT in Li, Ma and Xu (2015):
$$
\begin{aligned}
\Delta \ln X_{f p c t}=& \mu+\alpha_{x} \Delta \ln R E R_{c t}+\beta_{x} \Delta \ln R E R_{c t} \times \ln \varphi_{f t-1}+\gamma_{x} \ln \varphi_{f t-1} \\
&+\delta_{x} \Delta \ln \varphi_{f t}+\lambda_{x} \Delta \ln R G D P_{c t}+\xi_{f p c}+\tau_{t}+\varepsilon_{f p c t}
\end{aligned}
$$
The baseline empirical specification in CDV (2013):
$$
\ln p_{i j c t}=\mu_{i j c}+\Phi(t)+\beta \ln \left(R E R_{c t}\right)+X_{j t-1} \gamma+Z_{i c t} \delta+\varepsilon_{i j c t}
$$
The empirical specification regarding price adjustments for products within a firm in CDV (2013):
$$
\begin{aligned}
\ln p_{i j c t}=& \mu_{i j c}+\Phi(t)+\beta_{1} \ln \left(R E R_{c t}\right)+\beta_{2} \ln \left(R E R_{c t}\right) \times \text {Ladder}_{i j c t} \\
&+\ln \left(R E R_{c t}\right) \times X_{j t-1} \beta_{3}+X_{j t-1} \gamma+Z_{i c t} \delta+\varepsilon_{i j c t} .
\end{aligned}
$$
The empirical specification allowing producer price responsiveness to varying according to industry and destination characteristics in CDV (2013):
$$
\begin{aligned}
\ln p_{i j c t}=& \mu_{i j c}+\Phi(t)+X_{j t-1} \gamma+Z_{i c t} \delta \\
&+\beta_{1} \ln \left(R E R_{c t}\right)+\beta_{2} \ln \left(R E R_{c t}\right) \times \operatorname{Ladder}_{i j c t}+\ln \left(R E R_{c t}\right) \times X_{j t-1} \beta_{3} \\
&+\ln \left(R E R_{c t}\right) \times D e s t_{c t} \beta_{4}+\beta_{5} \ln \left(R E R_{c t}\right) \times \ln \left(D I S T M G_{i n d(i)}\right)+\varepsilon_{i j c t}
\end{aligned}
$$

## 2021/12/02

Reference article: The margins of global sourcing, theory, and evidence from US firms

Proposed topic: trade network response to exchange rate shocks

Two aspects of trade network response: export destination/import sources

Data source: raw customs data with ordinary trade from 2000-2007

Question: Are export companies more flexible in adjusting destinations or adjusting product types?

country profile change: c,t vs c,t-1

product profile change: p,t vs p,t-1

## 2021/12/07

An empirical method to identify the exchange rate shocks as exogenous: Bartik Instruments

Refer to Kohei's lecture note "14. Shift-share design"

- Goldsmith-Pinkham, P., Sorkin, I., & Swift, H. (2020). Bartik Instruments: What, when, why, and how. American Economic Review, 110(8), 2586–2624.

## 2021/12/20

Check if there is an aggregate declining overall passthrough pattern of Chinese exporters

Calculate product-country-year level passthrough

Do different industries have heterogeneous trends of passthrough change?

Firm credit constraint: tight vs loose

Credit constraint measure: Manova, R&D intensity, asset tangibility, inventory to sales

- Campa, Jos Manuel, and Linda S. Goldberg. 2005. Exchange Rate Pass-Through into Import Prices. The Review of Economics and Statistics, 87(4): 679-690.
- Fan, H., Lai, E. L. C., & Li, Y. A. (2015). Credit constraints, quality, and export prices: Theory and evidence from China. Journal of Comparative Economics, 43(2), 390–416.

Then we can try to link firm-level passthrough and firm-level credit constraints.

## 2022/01/03

Literature review about export price pass-through estimation:

**Campa and Goldberg (2005)**: ERPT into **import prices**, **aggregate** import price indices, 23 OECD countries;

To control for the shifting relative costs of a country’s aggregated trading partners, it constructs a consolidated export partners cost proxy as below:
$$
W_t^j=\frac{neu_t^j}{reu_t^j} \cdot P_t^j
$$
The short-run and long-run elasticities are given by lagged terms as below:
$$
\Delta p_{t}^{j}= \alpha+\sum_{i=0}^{4} a_{i}^{j} \Delta e_{t-i}^{j}+\sum_{i=0}^{4} b_{i}^{j} \Delta w_{t-i}^{j}+c^{j} \Delta g d p_{t}^{j}+\vartheta_{t}^{j}
$$
LCP (Local Currency Pricing) implies zero pass-through while PCP (Producer Currency Pricing) implies zero pass-through in the import ERPT case while the opposite for export ERPT. Over the long run, PCP is more prevalent for imported goods for OECD countries.

Country-specific exchange rate pass-through into import prices are significantly and positively correlated with inflation, money growth, and nominal exchange rate volatility.

The driving forces of aggregate pass-through evolution in OECD countries are shifts in the composition of country import bundles, i.e., increases in the relative manufacturing imports and declines in the relative raw materials and energy imports.

**Manova and Zhang (2013)**: six stylized facts about firms’ **export prices** using **Chinese customs data**

Export prices are measured by unit values in annual exports in the 2005 cross-section.

1. Across firms selling a given product, exporters that charge higher prices earn greater revenues in each destination, have bigger worldwide sales, and enter more markets.
2. Firms that export more, enter more markets, and charge higher export prices import more expensive inputs.
3. Across destinations within a firm-product pair, firms set higher prices in richer, larger, bilaterally more distant, and overall less remote countries.
4. Across destinations within a firm-product pair, firms earn bigger revenues in markets where they set higher prices.
4. Across firms within a product, exporters with more destinations offer a wider range of export prices.
6. Firms that export more, enter more markets, and offer a wider range of export prices pay a wider range of input prices and source inputs from more origin countries

Explanations: More successful exporters use higher quality inputs to produce higher quality goods (stylized facts 1 and 2), and firms vary the quality of their products across destinations by using inputs of different quality levels (stylized facts 3, 4, 5, and 6).

## 2022/01/05

The first-stage empirical tests focus on the country-level ERPT of China.

For the exchange rate index, I use the effective exchange rates (EERs) from the Bank for International Settlements (BIS). Both nominal and real EERs are calculated as geometric weighted averages of bilateral exchange rates, while the Real EERs are adjusted by relative consumer prices in the comparator countries. The weights are derived from manufacturing trade flows and capture both direct bilateral trade and third-market competition by double-weighting, based on Turner and Van’t dack (1993). (Refer to BIS EER notes)

For the trade price index, I primarily use the price level of exports (pl_x) of China from Penn World Table 10.0. (Refer to Feenstra, Inklaar and Timmer 2015). Besides, there are two alternative data sources: UNCTAD Export Unit Value Index (available from CEIC) and NBSC Price Indices of Imports and Exports of Commodity (available from China Statistical Yearbook). These alternative data can be used as references.

For empirical specification, we follow Campa and Goldberg (2005) to first construct short-run elasticities of exchange rate pass-through into aggregate export prices:
$$
\Delta p_{t}^{EX}= \alpha+ a \Delta REER_{t}^{CN}+ b \Delta w_{t}^*+c\Delta rgdp_{t}^{CN}+\vartheta_{t}
$$
All variables are expressed in the first differences of log terms. The real GDP series uses "rgdpna" in PWT 10.0, which means real GDP using national accounts growth rates, at constant 2017 national prices in 2017. The other control variable, trading-partner cost, is calculated using the above EERs from BIS data and price level of household consumption (pl_c) from PWT 10.0:
$$
W_t^*=\frac{NEER_t^{CN}}{REER_t^{CN}} \cdot P_t^{CN}
$$

| | Whole period | 1995-2002 | 2003-2010 | 2011-2019 |
| ---- | ------------ | --------- | --------- | ---------- |
| a | -0.4148*** | -0.1686 | -0.9714** | -0.7509*** |
| | (0.1435) | (0.1960) | (0.2603) | (0.1258) |
| b | 0.6547*** | 0.8301* | 1.0679*** | 0.6627*** |
| | (0.1379) | (0.3323) | (0.2176) | (0.0963) |
| c | 0.6232** | 1.5001** | 0.1722 | 0.9939*** |
| | (0.2279) | (0.3716) | (0.6183) | (0.2413) |

As a preliminary result, we can observe about 60% short-run export price pass-through over the whole period. However, we can not reject complete pass-through (or PCP) in the first period (1995-2002). In the second period (2003-2010), the export ERPT is smaller and closer to zero pass-through (or LCP), while in the last period it is about 25%.

## 2022/01/12

This week I revised the Chinese customs data from 2000-2007 to replicate Li, Ma, and Xu (2015)'s baseline specification:
$$
\Delta \ln p_{f p c t}=\mu+\alpha_{X} \Delta \ln R E R_{c t}+\beta_{X} \Delta \ln R G D P_{c t}+\xi_{f p c}+\tau_{t}+\varepsilon_{f p c t}
$$
For firm-level trade data, I calculate the unit value on the 6-digit HS product level as a proxy for the f.o.b. price. Since the value in the customs data is originally denoted by the US dollar, I use the current RMB-USD nominal exchange rate to calculate RMB-denominated prices.

For country-level exchange rate data, I use bilateral nominal exchange rate and price level of household consumption (price level of USA in 2017=1) from Penn World Table 10.0 to construct the real exchange rate.
$$
RER_{ct}=NER_{ct} \cdot \frac{CPI_{ct}}{CPI_{CHN,t}}
$$
To control for destination demand, I also real GDP (at constant 2017 national prices) from Penn World Table 10.0. To deal with possible non-stationarity, we use the first differences of log variables. Furthermore, I include firm–product–destination fixed effects to capture any time-invariant unobservable factors that are specific to the firm, product, destination, or their combinations. Year dummies are also included to control for macro-shocks common to all exporters.

In column (2), I perform a panel regression on the subsample of China's top destinations (49 economies with more than 10 billion USD export value from 2000-2007). In column (3), I run a similar regression weighted by transaction values. In columns (3)-(10), I run regressions with firm dummies year by year to check the trend of exchange rate pass-through over the sample period.

Estimations using both the whole customs data and the merged sample with CIE data show similar results as Li, Ma, and Xu (2015): Chinese exporters have very low pricing-to-market coefficients and a close-to-complete ERPT to export price. For the year-by-year results, the ERPT trend is not monotonic over the period. Instead, it shows a U-shape curve: coefficients for 2000 and 2007 are higher while 2001-2007 are closer to complete ERPT.

Although we do not find a declining passthrough in aggregate level, there may still be a declining passthrough in certain industries (products) or destination countries (currencies).

## 2022/01/18

**More literature review about credit constraint and export:**

- Manova, K. (2013). Credit constraints, heterogeneous firms, and international trade. Review of Economic Studies, 80(2), 711–744.

- Strasser, G. (2013). Exchange rate pass-through and credit constraints. Journal of Monetary Economics, 60(1), 25–38.

- Manova, K., Wei, S. J., & Zhang, Z. (2015). Firm exports and multinational activity under credit constraints. Review of Economics and Statistics, 97(3), 574–588.

**Manova (2013):** Credit constraints affect trade through 3 channels: the selection of heterogeneous firms into domestic production, the selection of domestic manufacturers into exporting, and the level of firm exports. In the model, firms need to pay up-front costs covered with external capital for export sales. There is a wedge between the productivity cut-offs for exporting with and without credit constraints. Moreover, firms with productivity below the cut-off at first-best levels will earn lower profits when both fixed and variable costs are under credit constraints. The empirical parts study how interactions of country measures of financial development (private credit, contract repudiation, accounting standards, risk of expropriation) and sector indicators of financial vulnerability (external finance dependence, asset tangibility) affect export.

**Strasser (2013):** Financially constrained firms pass-through exchange rate changes to prices at almost twice the rate of unconstrained firms, keeping pricing-to-market to a minimum. Similarly, their export volumes are about twice as sensitive to exchange rate fluctuations. The effect of borrowing constraints is particularly strong during the recent financial crisis. They use the ordered Probit model with the business survey data from the Ifo Manufacturing Survey in Germany with questions about planned export trade volume, domestic price changes, and credit constraints.

**Manova, Wei, and Zhang (2015)**: This paper finds foreign affiliates and joint ventures in China have better export performance than private domestic firms in financially more vulnerable sectors. It is consistent with multinational subsidiaries being less liquidity constrained because they can access foreign capital markets or funding from their parent company, They further suggest that FDI can alleviate the impact of domestic financial market imperfections on trade.

## 2022/01/21

Past literature explored three channels leading to incomplete export price pass-through.

The first channel is local currency pricing (LCP). As surveyed by Engel (2003), it means short-run nominal rigidities with prices sticky in the destination currency. Under LCP, the firms that do not adjust prices have zero short-run pass-through. Gopinath and Rigobon (2008) provide direct evidence on the extent of LCP in US import and export prices during 1994-2005.

The second channel is pricing-to-market (PTM). It is from variable markups in which firms optimally choose different prices depending on destination market conditions. Atkeson and Burstein (2008) provide a recent quantitative investigation of the PTM channel and its implication for aggregate prices. Berman, Martin, and Mayer (2012) find that high–performance firms react to a depreciation by increasing significantly more markup and by increasing less export volume. Manova and Zhang (2012) also support that variable mark-ups and product quality across destinations should be considered to explain ERPT patterns.

Gopinath, Itskhoki, and Rigobon (2010) about currency choice and Gopinath and Itskhoki (2010) about price adjustment frequency, further combine the above two channels. They show that the PTM and LCP channels of incomplete pass-through interact and reinforce each other, with highly variable-markup firms endogenously choosing to price in local currency as well as adopting longer price durations. If more firms were to adjust prices infrequently, the exchange rate pass-through would decline.

The third channel is the marginal production cost. While local distribution cost results in incomplete pass-through into consumer prices, the imported inputs channel by Amiti, Itskhoki, and Konings (2014) also get into producer factory gate prices. For example, an appreciation of home currency will decrease marginal costs due to cheaper imported inputs, thus partially offsetting the increases in export prices. The fact that large exporters are simultaneously large importers could help understand low aggregate exchange rate pass-through and the variation in pass-through across exporters.

Recent literature finds more firm-level evidence on heterogeneous pass-through. Chen and Juvenal (2014) predict more pricing-to-market and a smaller response of export volumes for higher quality goods and provide strong support with experts wine ratings to measure quality. Garetto (2016) gives two more arguments: 1) firm-level pass-through is a U-shaped function of firm-level productivity and market share; and 2) producers under incomplete information, such as new entrants, have lower pass-through rates than those under complete information. Auer and Schoenle (2016) also show that the response of import prices to exchange rate changes is U-shaped in exporter market share using micro-data. Devereux, Dong, and Tomlin's (2017)'s novel feature are that ERPT and currency invoicing depend on the market share of both importers (negative) and exporters (U-shaped). It confirms that very small or very large exporters have higher rates of pass-through and tend to invoice in the foreign currency.

Strasser (2013) contributes to the ERPT literature by incorporating credit constraints. He finds that financially constrained firms keep PTM to a minimum and pass-through exchange rate changes to prices at almost twice the rate of unconstrained firms, and their exports respond to exchange rate changes more strongly. This literature about credit constraints and trade should refer to Manova (2013) and Manova, Wei, and Zhang (2015). They study how interactions between countries' financial development and sectors' financial vulnerability affect export activity.

## 2022/01/23

I use the customs transaction data from 2000-2011 to check the baseline panel regressions.

Below are the graphs of declining pass-through with proxied by moving average coefficients with subsamples covered 3 years and 5 years, respectively:



## 2022/01/24

《强制结售汇制度退出历史舞台 企业和个人可自主保留外汇收入》——国家外汇管理局 2012-04-16

加入世界贸易组织以来，我国涉外经济快速发展，国际收支的主要矛盾逐渐由过去外汇短缺转为外汇储备增长过快。2002年至2011年，我国外汇储备年均增加近3000亿美元，是1994年至2001年年均增加额的12倍。顺应形势变化及市场主体实际需求，2001年起，我国通过改进外汇账户开立和限额管理，逐步扩大企业保留外汇自主权。

一是放宽企业开立外汇账户保留外汇的条件。2001年，允许符合年度出口收汇额等值200万美元以上、年度外汇支出额等值20万美元以上等条件的企业，经外汇管理部门批准后开立外汇结算账户，保留一定限额的货物出口、服务贸易等外汇收入。2002年，取消开户条件限制，凡有外贸经营权或经常项目外汇收入的企业，均可经外汇管理部门批准开立经常项目外汇账户。2006年，进一步取消开户事前审批，企业无需经外汇局批准即可直接到银行开立经常项目外汇账户。

二是提高外汇账户内保留外汇的限额。2002年，账户限额为企业上年度经常项目外汇收入的20%。2004年，提高到30%或50%。2005年，进一步提高到50%或80%。2006年，改变之前仅按收入核定限额的方法，按照企业上年度经常项目外汇收入的80%与经常项目外汇支出的50%之和核定限额，企业可保留的外汇限额进一步提高。2007年，取消账户限额管理，允许企业根据经营需要自主保留外汇。

2008年，修订后的《外汇管理条例》明确企业和个人可以按规定保留外汇或者将外汇卖给银行。2009年以来，为进一步促进贸易投资便利化，提高政策透明度，外汇管理部门大力开展法规清理，共宣布废止和失效400余个外汇管理规范性文件。涉及强制结售汇的规范性文件被宣布废止、失效或修订。目前，强制结售汇政策法规均已失去效力，实践中不再执行。

2008年修订《**中华人民共和国外汇管理条例**》http://www.gov.cn/zwgk/2008-08/06/content_1066085.htm

## 2022/01/25

**More recent literature about the decline in exchange rate pass-through:**

Bailliu, J., Dong, W., & Murray, J. (2010). Has Exchange Rate Pass-Through Really Declined? Some Recent Insights from the Literature. Bank of Canada Review, 1–8.

Gust, C., Leduc, S., & Vigfusson, R. (2010). Trade integration, competition, and the decline in exchange-rate pass-through. Journal of Monetary Economics, 57(3), 309–324.

**Bailliu, Dong, & Murray (2010)**: One reason for the decline in ERPT to import prices may be the increased trade integration because supply chains have become more interconnected and globalized. In addition, large importers have the significant market power to discriminate between suppliers based on location. An alternative explanation is that the composition of imports may have shifted towards sectors that have lower degrees of ERPT, i.e. away from commodities and towards sectors with higher degrees of product differentiation such as manufacturing. The final reason is the growing importance of emerging markets in the world economy. The decline in pass-through in advanced economies is consistent with a rise in the proportion of imports from emerging markets including China, where many firms adapt pricing-to-market (PTM). As anecdotal evidence of asymmetric ERPT, some of the most striking macro evidence of the weak correlation between exchange rates and inflation comes from cases in which prices respond by very little to large currency depreciation (Burstein, Eichenbaum, and Rebelo 2007).

This paper also lists pitfalls of reduced-form models where the inflation rate depends on current and lagged changes in the nominal exchange rate. First, in practice, exchange rates are determined by macro fundamentals endogenously. By assuming that exchange rates are exogenous, the reduced-form approach misses the important feedback effect from prices to interest rates and from interest rates to exchange rates, and back to prices. Second, reduced-form specifications rely on models with too little structure, which cannot attribute the extent of ERPT to specific factors, such as price stickiness. Finally, the reduced-form approach cannot identify how the degree of ERPT depends on the nature of shocks. By an open-economy DSGE model, ERPT remains larger than in reduced-form estimation and should be complete in the long run, but incomplete in the short run, owing to both nominal and real rigidities. As monetary policy responds more aggressively to expected inflation, measured short-run pass-through declines rapidly to zero.

**Gust, Leduc, and Vigfusson (2010)**: This macro paper follows the above literature review in the decline in exchange rate pass-through. The evidence confirms an increasing disconnect between the price of imported finished goods and the exchange rate. They claim that a significant portion of U.S. import price declines result from increased trade integration. With a two-country open economy DGE model featuring variable demand elasticities, a foreign exporter finds it optimal to vary its markup in response to exchange rate shocks. With increased trade integration, exporters have become more responsive to their competitors' prices, which in turn results in a sizeable decline in the sensitivity of U.S import prices to the exchange rate.

## 2022/01/26

**Detail discussion about U-shape ERPT function of productivity and market share:**

Garetto, S. (2016). Firms’ heterogeneity, incomplete information, and pass-through. Journal of International Economics, 101, 168–179.

Devereux, M. B., Dong, W., & Tomlin, B. (2017). Importers and exporters in exchange rate pass-through and currency invoicing. Journal of International Economics, 105, 187–204.

**Garetto (2016)**: This paper builds a trade model with strategic price setting under incomplete information. A supplier must choose its optimal price by considering both direct competitions from the producers of the same good and indirect competition from the producers of other, imperfectly substitutable goods in all countries. Since both the elasticity of demand and the optimal price are functions of the firm’s marginal cost, so is the ERPT pass-through. The extremely productive firm will have a CES constant mark-up, so its pass-through is complete; while an extremely unproductive firm with almost infinite demand elasticity tends to set price as perfectly competitive so that pass-through is also complete.

**Devereux, Dong, Tomlin (2017)**: They find that exchange rate pass-through and the currency of invoicing are dependent on the size (or market share) of both importers and exporters. Very small or very large exporters have higher rates of pass-through and tend to invoice in the foreign currency, while it is the opposite for exporters in the middle range, which is a non-monotonic U-shaped relationship. By contrast, for larger importers, pass-through is lower and local currency invoicing is more prevalent.

## 2022/01/29

**Details of constructing credit constraint measures in literature:**

**Manova, Wei, and Zhang (2015)**: This paper use multiple measures of sectors’ financial vulnerability, *FinVulni*, to capture different aspects of firms’ sensitivity to the availability of outside capital. They are available for 36 ISIC three-digit sectors, matched to Chinese HS 8-digit products.

1. **external finance dependence** (*ExtFin*): the share of capital expenditures not financed with cash flows from operations.
2. **inventories ratio** (*Invent*): the ratio of inventories to sales to proxy the duration of the production cycle and the liquidity needed to maintain inventories and meet demand.
3. **asset tangibility** (*Tang*): the availability of tangible assets that firms can pledge as collateral to raise finance with the share of plant, property, and equipment in total book value assets.
4. **trade credit intensity** (*TrCredit*): the ratio of the change in accounts payable to the change in total assets to characterize the availability and frequency of trade credit in an industry.

## 2022/02/03
To use measurements from the appendix table of Manova, Wei, and Zhang (2015), we need to match the CIC industry code system from CIE data to the ISIC (International Standard Industrial Classification)

1. Match ISIC Rev.3 to ISIC Rev.2 3-digit and 4-digit industries from Manova, Wei, and Zhang (2015).
2. Match CIC adjusted codes to ISIC Rev.3.
3. Match customs-CIE merged sample to the appendix table of MWZ (2015).

## 2022/02/05

I compute the first principal component of external finance dependence and asset tangibility following Manova, Wei, and Zhang (2015). It intuitively increases with ExtFin and falls with Tang, such that industries are more financially sensitive if they require more outside funds but dispose of less collateralizable assets.
$$
\Delta \ln p_{EX;fpct}=\alpha+\beta_{1} \Delta \ln RER_{ct}+\beta_{2} \Delta \ln RER_{ct} * FinVuln_{f}+\gamma \Delta \ln RGDP_{ct}+\xi_{fpc}+\tau_{t}+\varepsilon_{fpct}
$$
Below are the regression results of exchange rate pass-through with different measures of credit constraints. The preliminary results verified the conclusion of Strasser (2013) which argues financially constrained firms have higher export price pass-through compared to the unconstrained firms.

| | (1) | (2) | (3) | (4) |
| ----------------------- | -------- | -------- | ---------------- | ----------- |
| | Baseline | FPC | External Finance | Tangibility |
| dlnRER | 0.031*** | 0.035*** | 0.033*** | 0.002 |
| | (0.005) | (0.006) | (0.005) | (0.016) |
| dlnrgdp | -0.085** | -0.085** | -0.085** | -0.086** |
| | (0.036) | (0.036) | (0.036) | (0.036) |
| x_FPC | | 0.011** | | |
| | | (0.005) | | |
| x_ExtFin_US | | | -0.031** | |
| | | | (0.014) | |
| x_Tang_US | | | | 0.108* |
| | | | | (0.055) |
| Year FE | Yes | Yes | Yes | Yes |
| Firm-product-country FE | Yes | Yes | Yes | Yes |

## 2022/02/07

Today's task is to compute the four measures of credit needs based on Chinese firm-level information from CIE data.

Fan, H., Lai, E. L. C., & Li, Y. A. (2015). Credit constraints, quality, and export prices: Theory and evidence from China. Journal of Comparative Economics, 43(2), 390–416.

Li, Y. A., Liao, W., & Zhao, C. C. (2017). Credit constraints and firm productivity: Microeconomic evidence from China. Research in International Business and Finance, 45 (July 2017), 134–149.

1. external finance dependence (ExtFin): the share of capital expenditures not financed by cash flows from operations for each industry (cited from Fan, Lai, Li (2015) Table A.1)
2. inventories ratio (Invent): inventory/sales income (calculated using CIE)
3. asset tangibility (Tang): fixed assets/total assets (calculated using CIE)
4. R&D intensity: R&D spending/total sales income (only available for 2005-2007) (calculated using CIE)

| | (1) | (2) | (3) | (4) | (5) |
| ----------------------- | -------- | ---------------- | ----------- | --------- | ------------- |
| | Baseline | External Finance | Tangibility | Inventory | R&D Intensity |
| dlnRER | 0.031*** | 0.021*** | -0.026 | 0.073*** | 0.039*** |
| | (0.005) | (0.007) | (0.024) | (0.020) | (0.007) |
| dlnrgdp | -0.084** | -0.083** | -0.084** | -0.083** | -0.083** |
| | (0.036) | (0.036) | (0.036) | (0.036) | (0.036) |
| x_ExtFin_cic2 | | -0.014** | | | |
| | | (0.007) | | | |
| x_Tang_cic2 | | | 0.191** | | |
| | | | (0.077) | | |
| x_Invent_cic2 | | | | -0.387** | |
| | | | | (0.174) | |
| x_RDint_cic2 | | | | | -0.462* |
| | | | | | (0.253) |
| Year FE | Yes | Yes | Yes | Yes | Yes |
| Firm-product-country FE | Yes | Yes | Yes | Yes | Yes |

## 2022/02/17

For robustness checks, we allow some credit constraint measures from CIE (tangibility, inventory, and R&D intensity) to change over time. The interaction term coefficients exhibit the same signs as above. We can conclude that financially more constrained firms have more complete export exchange rate pass-through than those less constrained.

To further ask whether the declining trend of exchange rate pass-through was at least partially affected by credit constraints, there are two possible channels to discuss:

1. The credit constraints on Chinese exporters are gradually loosening. It may be because of the decreasing credit needs of Chinese exporters or the improvement of the immature financial market in China.
2. China's exports switch from more credit-constrained to less-constrained industries. Credit-constrained firms find it harder to survive in export markets (extensive margin) or export less in value (intensive margin).

## 2022/02/23

Two paper published in 2021 about the export response to exchange rate shocks and credit constraints using Chinese data:

Dai, M., Nucci, F., Pozzolo, A. F., & Xu, J. (2021). Access to finance and the exchange rate elasticity of exports. Journal of International Money and Finance, 115, 102386.

Xu, Y., & Guo, Y. (2021). Exchange rate disconnect and financial constraints —evidence from Chinese firms. Journal of Comparative Economics, 49(4), 1008–1019.

**Dai, Nucci, Pozzolo, and Xu (2021)**: They find that exporting activities by more financially constrained firms are more sensitive to exchange rate changes than those by firms with a better ability to raise external capital. Besides the result on export volumes, the exchange rate pass-through to export prices denominated in the domestic currency is lower for firms facing stronger financial constraints.

Its baseline specification estimating the differential impact of exchange rates fluctuations on exports depending on the firm’s ability to have access to finance is the following (replace export volume with an export status dummy for extensive margin):
$$
\begin{aligned}
\ln \left(\text{Export volume}_{it}\right)=& \beta_{0}+\beta_{1} \ln \left(\text {Exchange rate}_{jt}\right)+\beta_{2}\left(\text {Access to Finance}_{it-1}\right) \\
&+\beta_{3} \ln \left(\text {Exchange rate}_{jt}\right) \times\left(\text {Access to Finance}_{it-1}\right) \\
&+\beta_{4} \ln \left(\text {Labor productivity}_{it-1}\right)+\gamma^{\prime} Z_{it}+\lambda_{i}+\psi_{t}+u_{it}
\end{aligned}
$$
**Xu, Guo (2021)**: They find that for sectors with large financial constraints, the response in export is small, while for less financially constrained sectors, the response can be larger. The estimated elasticity decreases with the sector’s degree of financial constraints. At the firm level, they find that at the intensive margin, financial constraints restrict the firm’s export value to the existing destination market; at the extensive margin, financial constraints restrict the number of firms participating in exporting, the number of firm-product pairs being exported, and the probability of entering a new destination market.

The baseline regressions at the sector level and firm level are as below respectively:
$$
\ln \left(\mathrm{EXP}_{sct}\right)=\alpha+\beta \ln \left(RER_{c t}\right)+\gamma \ln \left(RER_{ct}\right) \times \text {FinCons}_{s}+Z_{ct}+\mu_{sc}+\varphi_{t}+\varepsilon_{sct}
$$

$$
\ln \left(\mathrm{EXP}_{fsct}\right)=\alpha+\beta \ln \left(RER_{ct}\right)+\gamma \ln \left(RER_{ct}\right) \times \text {FinCons}_{fs}+Z_{ct}+\mu_{fsc}+\varphi_{t}+\varepsilon_{fsct}
$$

## 2022/02/24

Two theoretical papers about credit constraint and export cited by recent studies:

Feenstra, R. C., Li, Z., & Yu, M. (2014). Exports and credit constraints under incomplete information: Theory and evidence from China. Review of Economics and Statistics, 96(4), 729–744.

Chaney, T. (2016). Liquidity constrained exporters. Journal of Economic Dynamics and Control, 72(March 2005), 141–154.

## 2022/02/27

**Perspective about import market share and pass-through over time:**

Devereux, M. B., Dong, W., & Tomlin, B. (2017) Appendix F runs the below regression on 12-month windows moving up one month at a time covering 70 months.
$$
\Delta_{\tau} p_{s t}=c+\beta_{e} \triangle_{\tau} e_{s t}+Z_{s t}^{\prime} \gamma+\epsilon_{s t}
$$
where $\triangle_{\tau} p_{s t}=\ln \left(P_{s t}\right)-\ln \left(P_{s \tau}\right)$ is expressed in home currency and $\tau$ represents the last period in which this price is observed (a good will not necessarily be imported every period).

They present the value-weighted pass-through estimates and the share of the total value of imports accounted for by importers and exporters that fall within the third to fifth quintiles of the import market share distribution. The general trends suggest that the larger the import market share of large importers, the lower is overall pass-through.

## 2022/02/28

Using the import customs data, I replicate the specifications as in Feb 2, to calculate the **import** exchange rate passthrough and credit constraint.
$$
\Delta \ln p_{IM;fpct}=\alpha+\beta_{1} \Delta \ln RER_{ct}+\beta_{2} \Delta \ln RER_{ct} * FinVuln_{f} + \gamma \Delta \ln RGDP_{ct}+\xi_{fpc}+\tau_{t} +\varepsilon_{fpct}
$$

| | (1) | (2) | (3) | (4) |
| ----------------------- | -------- | --------- | ---------------- | ----------- |
| | Baseline | FPC | External Finance | Tangibility |
| dlnRER | 0.359*** | 0.290*** | 0.318*** | 0.601*** |
| | (0.015) | (0.017) | (0.016) | (0.036) |
| dlnrgdp | 0.264*** | 0.281*** | 0.283*** | 0.271*** |
| | (0.090) | (0.090) | (0.090) | (0.090) |
| x_FPC_US | | -0.111*** | | |
| | | (0.011) | | |
| x_ExtFin_US | | | 0.335*** | |
| | | | (0.033) | |
| x_Tang_US | | | | -0.978*** |
| | | | | (0.130) |
| Year FE | Yes | Yes | Yes | Yes |
| Firm-product-country FE | Yes | Yes | Yes | Yes |

| | (1) | (2) | (3) | (4) | (5) |
| ----------------------- | -------- | ---------------- | ----------- | --------- | ------------- |
| | Baseline | External Finance | Tangibility | Inventory | R&D Intensity |
| dlnRER | 0.359*** | 0.363*** | 0.800*** | 0.048 | 0.239*** |
| | (0.015) | (0.018) | (0.059) | (0.048) | (0.020) |
| dlnrgdp | 0.264*** | 0.264*** | 0.259*** | 0.285*** | 0.279*** |
| | (0.090) | (0.090) | (0.090) | (0.090) | (0.090) |
| x_ExtFin_cic2 | | 0.007 | | | |
| | | (0.016) | | | |
| x_Tang_cic2 | | | -1.520*** | | |
| | | | (0.195) | | |
| x_Invent_cic2 | | | | 2.738*** | |
| | | | | (0.397) | |
| x_RDint_cic2 | | | | | 6.214*** |
| | | | | | (0.649) |
| Year FE | Yes | Yes | Yes | Yes | Yes |
| Firm-product-country FE | Yes | Yes | Yes | Yes | Yes |

We can see that the import ERPT of China is around 35.9%, which is much lower compared to the export ERPT (96.9%). For most specifications except Table B column (2), the import ERPT is higher for firms in more financial vulnerable industries (i.e. higher external finance dependence, lower asset tangibility, high inventory ratio or high R&D intensity).

Therefore, we can reach a similar conclusion as in the export case that import prices in sectors with large financial constraints are more sensitive to exchange rate shocks (lower import ERPT).

## 2022/03/01

The next task is to incorporate market share measures into our dataset following Amiti, Itskhoki, and Konings (2014) and Devereux, Dong, and Tomlin (2017).
$$
\begin{aligned}
\Delta \ln p_{EX;fpct}=&\alpha+\beta_{1} \Delta \ln RER_{ct}+\beta_{2} \Delta \ln RER_{ct} * FinVuln_{f}+\beta_{3} \Delta \ln RER_{ct} * S_{EX;fpct} \\
+&\beta_{4} [\Delta \ln RER_{ct} * S_{EX;fpct}]^2 + \gamma \Delta \ln RGDP_{ct}+\xi_{fpc}+\tau_{t} +\varepsilon_{fpct}
\end{aligned}
$$

$$
\begin{aligned}
\Delta \ln p_{IM;fpct}=&\alpha+\beta_{1} \Delta \ln RER_{ct}+\beta_{2} \Delta \ln RER_{ct} * FinVuln_{f}+\beta_{3} \Delta \ln RER_{ct} * S_{IM;fpct} \\
+&\beta_{4} [\Delta \ln RER_{ct} * S_{IM;fpct}]^2 + \gamma \Delta \ln RGDP_{ct}+\xi_{fpc}+\tau_{t} +\varepsilon_{fpct}
\end{aligned}
$$
We define import (or export) market share as a given firm’s share of the import (or export) market, in terms of value, within a given HS6 product category, in a certain year. Therefore, a single firm can have multiple import (or export) market shares if they import (or export) multiple products and a firm’s import (or export) market share can vary over time.
$$
S_{IM;fpct} \equiv \frac{\text {Import value}_{fpct}}{\sum_{f^{\prime} \in F_{pct}} \text {Import value}_{f^{\prime}pct}}
$$

$$
S_{EX;fpct} \equiv \frac{\text {Export value}_{fpct}}{\sum_{f^{\prime} \in F_{pct}} \text {Export value}_{f^{\prime}pct}}
$$

## 2022/03/07

The results of regressions with import or export market shares are in the below table

| | (1) | (2) | (3) | (4) |
| ----------------------- | --------- | -------- | -------- | -------- |
| | Export | Export | Import | Import |
| dlnRER | 0.045*** | 0.039*** | 0.372*** | 0.375*** |
| | (0.007) | (0.007) | (0.016) | (0.017) |
| dlnrgdp | -0.069* | -0.070* | 0.260*** | 0.259*** |
| | (0.037) | (0.037) | (0.090) | (0.090) |
| Market Share | 0.072*** | 0.072*** | -0.004 | -0.004 |
| | (0.004) | (0.004) | (0.012) | (0.012) |
| x_MS | -0.042*** | 0.063 | -0.111** | -0.207 |
| | (0.013) | (0.049) | (0.044) | (0.162) |
| x_MS^2 | | -0.111** | | 0.110 |
| | | (0.050) | | (0.178) |
| Year FE | Yes | Yes | Yes | Yes |
| Firm-product-country FE | Yes | Yes | Yes | Yes |

The preliminary results show that for Chinese exporters with larger market shares tend to have more complete pass-through while Chinese importers with larger market shares usually have more incomplete pass-through. The negative relationship between import ERPT and market share is roughly consistent with Devereux, Dong, Tomlin (2017) while the export ERPT does not show a clear U-shape relationship.

## 2022/03/08

Today I calculate pass-through across exporters (importers) within quintiles of the market share distribution.

| Export | (1) | (2) | (3) | (4) | (5) |
| ----------------------- | -------- | -------- | ------- | ------- | ------- |
| | 1st | 2nd | 3rd | 4th | 5th |
| dlnRER | 0.089*** | 0.105*** | 0.024* | 0.026** | 0.005 |
| | (0.030) | (0.019) | (0.015) | (0.011) | (0.009) |
| dlnrgdp | -0.069 | 0.167 | -0.009 | -0.091 | -0.019 |
| | (0.211) | (0.133) | (0.102) | (0.075) | (0.058) |
| Year FE | Yes | Yes | Yes | Yes | Yes |
| Firm-product-country FE | Yes | Yes | Yes | Yes | Yes |
| N | 326914 | 359391 | 372477 | 381163 | 356102 |

| Import | (1) | (2) | (3) | (4) | (5) |
| ----------------------- | -------- | -------- | -------- | -------- | -------- |
| | 1st | 2nd | 3rd | 4th | 5th |
| dlnRER | 0.254*** | 0.353*** | 0.363*** | 0.390*** | 0.209*** |
| | (0.062) | (0.052) | (0.044) | (0.034) | (0.022) |
| dlnrgdp | -0.232 | -0.030 | 0.709*** | 0.232 | -0.231 |
| | (0.359) | (0.298) | (0.247) | (0.191) | (0.142) |
| Year FE | Yes | Yes | Yes | Yes | Yes |
| Firm-product-country FE | Yes | Yes | Yes | Yes | Yes |
| N | 324778 | 349909 | 365048 | 376546 | 377514 |

From the coefficients of the sub-samples divided by market share quintiles, we see as we increase the import market share, pass-through at first increases from 0.254 (the 1st quintile) to 0.390 (the 4th quintile) but finally drops to 0.209 (the 5th quintile).

On the other hand, if we increase the export market share, passthrough will decrease from 0.911 (the 1st quintile) to 0.895 (the 2nd quintile), and increase to 0.974 (the 4th quintile) and eventually close to complete (the 5th quintile). We can observe approximate (but not perfect) U-shape in both cases.

## 2022/03/09

**Two papers recommended by Prof. Li about forward exchange rate and trade:**

Li, Y. A., & Zhao, C. C. (2016). Price Adjustment to Exchange Rates and Forward-looking Exporters: Evidence from USA–China Trade. Review of International Economics, 24(5), 1023–1049.

Fan, H., Li, Y. A., & Zhao, C. C. (2018). Margins of imports, forward-looking firms, and exchange rate movements. Journal of International Money and Finance, 81(71603155), 185–202.

**Li and Zhao (2016)**: In the presence of sticky prices, firms incorporate expectations of future exchange rate changes into their current pricing decisions (a "forward-looking nature"). As a result, the expectations of future exchange rates affect current prices at both the product level and firm level. They find that the trade price response to expected future exchange rate changes accounts for approximately over one-third of the total “pass-through” coefficient.

**Fan, Li, and Zhao (2018)**: The impact of future exchange rate on import is different from that of current exchange rate: spot exchange rate appreciation would increase both the intensive margin (import value of individual firm) and the extensive margin (the number of importing firms), while future exchange rate appreciation increases the extensive margin rather than the intensive margin of imports.

## 2022/03/11

Meeting notes:

Add contract intensity (the third element) in export/import ERPT and credit constraint

Contract intensity measures: by-sector and by-country (rule-of-law indicator)

Also try global value chain upstreamness of Chinese exporters

## 2022/03/12

Two papers about contract intensity and GVC upstreamness:

Nunn, N. (2007). Relationship-specificity, incomplete contracts, and the pattern of trade. Quarterly Journal of Economics, 122(2), 569–600.

Chor, D., Manova, K., & Yu, Z. (2021). Growing like China: Firm performance and global production line position. Journal of International Economics, 130, 103445.

## 2022/03/20

**Nunn (2007)**'s contract intensity measures are originally classified according to 3-digit ISIC Rev. 2 system. To match this measure with CIE data, I construct a concordance from ISIC Rev. 2 to ISIC Rev. 3 and then another concordance from ISIC Rev. 3 to the (adjusted) CIC industry codes, which is similar to the steps as dealing with MWZ (2015). The original dataset is downloaded from Nathan Nunn's website. https://scholar.harvard.edu/nunn/pages/data-0

The variables "RS" stands for “relationship-specific. Both RS1 and RS2 measures classify inputs that are neither bought and sold on an exchange nor reference priced as being relationship-specific, but RS2 also includes reference priced inputs as being relationship-specific.
$$
\begin{gathered}
z_{i}^{r s 1}=\sum_{j} \theta_{i j} \boldsymbol{R}_{j}^{\text {neither }} \\
z_{i}^{r s 2}=\sum_{j} \theta_{i j}\left(R_{j}^{\text {neither }}+R_{j}^{\text {ref price }}\right)
\end{gathered}
$$
**Chor, Manova and Yu (2021)**'s industry upstreamness measures are originally based on the 2007 China IO Tables. After matching to HS6 product level, they could be integrated into our customs records. Conceptually, the upstreamness of industry i, Ui, is a weighted average of the number of stages from final demand at which i enters as an input in production processes.

In an economy with N ≥ 1 industries, we calculate Ui as follows:
$$
U_{i}=1 \cdot \frac{F_{i}}{Y_{i}}+2 \cdot \frac{\sum_{j=1}^{N} d_{i j} F_{j}}{Y_{i}}+3 \cdot \frac{\sum_{j=1}^{N} \sum_{k=1}^{N} d_{i k} d_{k j} F_{j}}{Y_{i}}+4 \cdot \frac{\sum_{j=1}^{N} \sum_{k=1}^{N} \sum_{l=1}^{N} d_{i l} d_{l k} d_{k j} F_{j}}{Y_{i}}+\ldots
$$

## 2022/03/22

**Alternative firm-level measures of financial constraints:**

Dai, Nucci, Pozzolo, and Xu (2021) uses three time-varying indicators to capture the firm’s ability to access finance:

1. **Cash ratio**: the ratio of cash holdings to total assets. Cash holdings are computed as current assets net of inventories and accounts receivable (Love, 2003)
2. **Liquidity ratio**: the ratio of net liquidity to total assets; The amount of net liquid assets is computed as current assets minus current liabilities (Manova and Yu, 2016)
3. **Leverage ratio**: the ratio of debt to total assets. We take the inverse of the ratio of total debt over total assets to ensure that an increase in each indicator represent a decrease, a relaxation of financing constraints.

These variables enter the specification with a one-period lag to mitigate the problems arising from their possible endogeneity.

## 2022/04/01

Financial constraint, contract intensity and upstreamness will all affect import exchange rate passthrough, both independently and jointly. In short, high contract intensity will reinforce the positive effect of credit constraint on import ERPT while high upstreamness will mitigate this effect. Those same tests do not yield significant results for Chinese exporters. The results of contract intensity are not attached here.

The specification including product-level upstreamness is attached as below:
$$
\Delta \ln p_{IM;fpct}=\alpha+\beta_{1} \Delta \ln RER_{ct}+\beta_{2} \Delta \ln RER_{ct} * FinVuln_{f} +\beta_{3} \Delta \ln RER_{ct} * U^{M}_{p}\\
+\gamma \Delta \ln RGDP_{ct}+b\chi_{ft}+\xi_{fpc}+\tau_{t} +\varepsilon_{fpct}
$$

| | (1) | (2) | (3) | (4) | (5) |
| ----------------------- | --------- | -------- | --------- | --------------- | ------------- |
| | Upstream | ExtFin | Tang | ExtFin*Upstream | Tang*Upstream |
| dlnRER | 1.321*** | 0.348*** | 0.624*** | 1.187*** | 1.920*** |
| | (0.049) | (0.016) | (0.035) | (0.052) | (0.152) |
| dlnrgdp | 0.382*** | 0.377*** | 0.363*** | 0.398*** | 0.386*** |
| | (0.088) | (0.088) | (0.088) | (0.088) | (0.088) |
| x_ups_HS6 | -0.245*** | | | -0.221*** | -0.354*** |
| | (0.012) | | | (0.013) | (0.039) |
| x_ExtFin_US | | 0.372*** | | 0.786*** | |
| | | (0.032) | | (0.139) | |
| x_Tang_US | | | -0.922*** | | -2.431*** |
| | | | (0.128) | | (0.566) |
| x_ExtFin_US_ups_HS6 | | | | -0.123*** | |
| | | | | (0.036) | |
| x_Tang_US_ups_HS6 | | | | | 0.441*** |
| | | | | | (0.144) |
| Year FE | Yes | Yes | Yes | Yes | Yes |
| Firm-product-country FE | Yes | Yes | Yes | Yes | Yes |
| N | 1648326 | 1648326 | 1648326 | 1648326 | 1648326 |

## 2022/04/03

Meeting Notes:

Let's leave the contract intensity for now and mainly focus on GVC upstreamness.

Next we construct firm-level upstreamness measures following Chor, Manova and Yu (2021).

Revisit the literature to find out mechanism/explanations about how credit constraints affect exchange rate pass-through.

Compare the different effects of GVC upstreamness on the relationship between credit constraints and ERPT.

## 2022/04/08

Explanations of the effects of credit constraints on ERPT:

**Strasser (2013):** His result suggests that unconstrained firms intentionally absorb more import price shocks to maintain their optimal domestic pricing policy. That is these firms price to market to their domestic market. By contrast, financially constrained firms have fewer margins to adopt pricing-to-market strategies and absorb exchange rate swings into the markups, so they have to keep PTM to a minimum.

**Dai, Nucci, Pozzolo, and Xu (2021)**: Following Strasser (2013), borrowing constraints force firms to keep pricing-to-market decisions to a minimum as they do not have enough margin to absorb an exchange rate shock on their markup.

Since a higher external finance premium causes the marginal costs to be higher, firms with more severe financial constraints tend to set higher prices and therefore, with a linear demand function, face a higher price elasticity of demand. Thus, with markup values endogenously determined in the model, an exchange rate depreciation allows firms to increase their markups but the credit-constrained firms do so only to a limited extent because they have fewer margins to adjust their profit margins.

**Xu, Guo (2021)**: Why does financial constraint matter? First, firms need to incur fixed costs, often paid in the currency of the destination country, to enter the foreign market (Chaney, 2016). Second, many firms hold both domestic and foreign assets; thus, the exchange rate fluctuations will change their capacity of pledging collateral (Kohn et al., 2020). Finally, with capital account liberalization, firms may also finance their fixed and/or variable production costs through the international market. Therefore, an appreciation will increase a firm's asset value in home currency, and decrease its export cost and debt value in foreign currency, thus, alleviating its financial burden, which may promote exports.

However, in response to the markup channel as in BMM (2012), they found that the effect of financial constraints remains robust and significant besides the markup adjustment. The estimated pricing-to-market coefficients are moderate for Chinese firms. This suggests the possibility of other factors at work as well, and the financial constraints factor is the one we reveal in this paper.

## 2022/04/14

Today my task is to construct firm-level upstreamness measures following Chor, Manova and Yu (2021). We compute a weighted-average upstreamness of firm’s imports:
$$
U_{f t}^{M}=\sum_{i=1}^{N} \frac{M_{f p t}}{M_{f t}} U_{i}
$$
where $M_{f t}=\sum_{i=1}^{N} M_{f p t}$ is firm's total imports in all industry.

Now we have a new specification as below:
$$
\Delta \ln p_{IM;fpct}=\alpha+\beta_{1} \Delta \ln RER_{ct}+\beta_{2} \Delta \ln RER_{ct} * FinVuln_{f} +\beta_{3} \Delta \ln RER_{ct} * U^{M}_{ft}\\
+\gamma \Delta \ln RGDP_{ct}+b\chi_{ft}+\xi_{fpc}+\tau_{t} +\varepsilon_{fpct}
$$

| | (1) | (2) | (3) | (4) | (5) |
| ----------------------- | --------- | -------- | --------- | --------------- | ------------- |
| | Upstream | ExtFin | Tang | ExtFin*Upstream | Tang*Upstream |
| dlnRER | 0.626*** | 0.348*** | 0.624*** | 0.499*** | 0.568** |
| | (0.070) | (0.016) | (0.035) | (0.074) | (0.229) |
| dlnrgdp | 0.372*** | 0.377*** | 0.363*** | 0.371*** | 0.370*** |
| | (0.088) | (0.088) | (0.088) | (0.088) | (0.088) |
| x_ups_firm | -0.062*** | | | -0.038** | 0.012 |
| | (0.018) | | | (0.019) | (0.061) |
| x_ExtFin_US | | 0.372*** | | -0.631*** | |
| | | (0.032) | | (0.217) | |
| x_Tang_US | | | -0.922*** | | -0.168 |
| | | | (0.128) | | (0.809) |
| x_ExtFin_US_ups_firm | | | | 0.275*** | |
| | | | | (0.059) | |
| x_Tang_US_ups_firm | | | | | -0.188 |
| | | | | | (0.213) |
| Year FE | Yes | Yes | Yes | Yes | Yes |
| Firm-product-country FE | Yes | Yes | Yes | Yes | Yes |
| N | 1648326 | 1648326 | 1648326 | 1648326 | 1648326 |

## 2022/04/26

Since our purpose is to study how Chinese importers adjust (or affect) import prices in response to exchange rate fluctuations, we need to separate the impact of export pricing, so we further try alternative specifications as the following:

First, we separate Chinese importers in our dataset into two subsamples: two-way traders (who both import and export in the same year) and one-way traders (who only import but not export in a certain year).

Second, since the sub-sample of one-way importers has a much smaller size, I relax the group fixed effect from the firm-product-country pairs to firm-sector-country pairs, where sectors are defined by HS2 rather than HS6 product codes. This increases the degrees of freedom, allowing for greater within-group variation.

## 2022/04/28

Since most of China's imports are done by two-way traders, the import exchange rate pass-through is also likely to be affected by export pass-through. Specifically, importers can pass on part of the price fluctuations of imported intermediate goods caused by exchange rate shocks to the export destination to reduce the impact of exchange rate risks. Therefore, after we calculate both import and export price pass-through at the firm level, we can compare the differences between these two ("exchange rate absorption") of different firms.

We argue that "exchange rate absorptive capacity" may be related to the firm's own attributes, such as credit constraints and value chain upstreamness, as discussed earlier. In the following work, we will control for those production factors (such as markup and productivity) to test these conjectures concretely.

## 2022/04/30

**Three papers on estimating productivity and markups**:

Brooks, W. J., Kaboski, J. P., & Li, Y. A. (2021). Agglomeration, Misallocation, and (the Lack of) Competition†. American Economic Journal: Macroeconomics, 13(4), 483–519.

De Loecker, J., & Warzynski, F. (2012). Markups and firm-level export status. American Economic Review, 102(6), 2437–2471.

Ackerberg, D. A., Caves, K., & Frazer, G. (2015). Identification Properties of Recent Production Function Estimators. Econometrica, 83(6), 2411–2451.

According to Brooks, Kaboski, and Li (2021), we need to construct four production variables (in log form): real output value (y_output), persons engaged (l), and real fixed assets at current value (k), and real material inputs (m). In practice, real output values are deflated by output deflators, while real fixed assets and real material inputs are deflated by investment deflators and input deflators, respectively.

## 2022/05/07

The regression specification with markup and TFP measures:
$$
\Delta \ln p_{IM;fpct}=[\alpha+\beta \cdot FinVuln_{f}+\gamma \cdot Markup_{ft}+\eta \cdot TFP_{ft}]*\Delta \ln RER_{ct} \\
+b \cdot \Delta \ln RGDP_{ct}+ c \cdot Markup_{ft}+d \cdot TFP_{ft}+\xi_{fpc}+\tau_{t} +\varepsilon_{fpct}
$$

| | (1) | (2) | (3) | (4) | (5) |
| ----------------------- | -------- | -------- | --------- | --------- | --------- |
| dlnRER | 0.390*** | 0.393*** | 1.257*** | 1.106*** | 1.375*** |
| | (0.047) | (0.015) | (0.071) | (0.075) | (0.075) |
| dlnrgdp | 0.370*** | 0.366*** | 0.401*** | 0.406*** | 0.402*** |
| | (0.090) | (0.088) | (0.090) | (0.090) | (0.090) |
| x_Markup_DLWTLD | -0.001 | | -0.648*** | -0.556*** | -0.620*** |
| | (0.034) | | (0.052) | (0.054) | (0.053) |
| x_tfp_tld | | 0.244*** | 1.180*** | 1.032*** | 1.137*** |
| | | (0.034) | (0.074) | (0.077) | (0.075) |
| x_ExtFin_US | | | | 0.225*** | |
| | | | | (0.034) | |
| x_Tang_US | | | | | -0.625*** |
| | | | | | (0.131) |
| Year FE | Yes | Yes | Yes | Yes | Yes |
| Firm-product-country FE | Yes | Yes | Yes | Yes | Yes |
| N | 1601909 | 1648326 | 1601909 | 1601909 | 1601909 |

$$
\Delta \ln p_{EX;fpct}=[\alpha+\beta \cdot FinVuln_{f}+\gamma \cdot Markup_{ft}+\eta \cdot TFP_{ft}]*\Delta \ln RER_{ct} \\
+b \cdot \Delta \ln RGDP_{ct}+ c \cdot Markup_{ft}+d \cdot TFP_{ft}+\xi_{fpc}+\tau_{t} +\varepsilon_{fpct}
$$

| | (1) | (2) | (3) | (4) | (5) |
| ----------------------- | --------- | -------- | -------- | -------- | --------- |
| dlnRER | -0.033 | 0.033*** | 0.034 | 0.047 | 0.009 |
| | (0.024) | (0.005) | (0.037) | (0.038) | (0.040) |
| dlnrgdp | -0.098*** | -0.082** | -0.096** | -0.095** | -0.096*** |
| | (0.037) | (0.037) | (0.037) | (0.037) | (0.037) |
| x_Markup_DLWTLD | 0.051*** | | 0.002 | -0.006 | 0.001 |
| | (0.018) | | (0.028) | (0.028) | (0.028) |
| x_tfp_tld | | 0.039** | 0.084** | 0.098*** | 0.086** |
| | | (0.016) | (0.035) | (0.036) | (0.035) |
| x_ExtFin_US | | | | -0.025* | |
| | | | | (0.015) | |
| x_Tang_US | | | | | 0.098* |
| | | | | | (0.058) |
| Year FE | Yes | Yes | Yes | Yes | Yes |
| Firm-product-country FE | Yes | Yes | Yes | Yes | Yes |
| N | 1623388 | 1647384 | 1623388 | 1623388 | 1623388 |

## 2022/05/08

For import ERPT, we can observe that importers with higher TFP will have more complete pass-through, while those with higher markup levels will have lower pass-through once we control their TFP. The negative effect of the markup level itself and the positive effect of TFP will cancel each other out. Credit constraints will still affect import pass-through if we control both markup and TFP.

For export ERPT, we can observe that exporters with higher TFP or higher markup levels will have lower pass-through, while this effect of markup levels will become insignificant once we control their TFP.

The above results are robust if we limit our sample to two-way traders.

Now the question is, why would the productivity and the markups of importers affect their exchange rate pass-through? Is the mechanism for import pass-through different compared to that for exporters?

## 2022/05/09

**Discussion about the relationship between import and export pass-through:**

On the one hand, for two-way traders, export exchange rate pass-through could act as a "pressure-reducing valve" for import price pass-through. When a firm has the ability to pass more exchange rate fluctuations to destination prices, it has more room to absorb price fluctuations of imported inputs. In other words, the firm-level export pass-through will have a positive effect on all product-level import pass-throughs of the same firm.

On the other hand, big importers are also big exporters (AIK, 2014). Therefore, advantages in some firm characteristics (such as size, market share, or productivity) may lead them to have greater bargaining power on both the import side and the export side and thus cause lower export and import price pass-through at the same time. This provides a direct channel for the determination of import pass-through.

From BMM (2012), more productive firms react to depreciation (or appreciation) by adjusting more markup and less export volume, keeping local market prices relatively stable, which means a less complete pass-through. After controlling for productivity, if a firm's markup is already high, the scope for further adjustment of markup may be limited. That is to say, TFP and markup levels could affect exchange rate pass-through in different directions.

To study whether and how those two channels affect the import exchange rate pass-through, ideally we need to control export price pass-through when calculating import price pass-through for all two-way traders. However, it is not available to accurately estimate the price pass-through of each individual firm. Therefore, we could only check those potential influential factors individually in our specifications.

## 2022/05/11

$$
\Delta \ln p_{IM;fpct}=[\alpha+\beta \cdot FinVuln_{f}+\gamma \cdot Markup_{ft-1}]*\Delta \ln RER_{ct} \\
+b \cdot \Delta \ln RGDP_{ct}+ c \cdot Markup_{ft-1}+d \cdot TFP_{ft-1}+\xi_{fpc}+\tau_{t} +\varepsilon_{fpct}
$$

**The brief structure for MPhil Thesis:**

1. import pass-through summary and trend
2. compare the difference between import and export ERPT patterns
3. How credit constraints affect import ERPT?
4. Why import ERPT is also affected by credit constraint?
1. bargaining power, markup
2. quality adjustment, lower cost inputs
5. CN measure (initial year as IV) and US measure of credit constraints

## 2022/05/17

### Research Progress

This project aims to study the patterns and the determinants of import exchange rate pass-through.

First, I calculated the import exchange rate pass-through as the price elasticity of import prices with respect to real exchange rates using Chinese firm-level data. Specifically, I merged the Chinese Industrial Enterprises datasets with the China customs records. Using the merged sample, I adopted a fixed effect panel regression specification with first order differences to capture the changes of product prices and real exchange rates. The average import exchange rate pass-through is between 35%-40%, which is rather incomplete compared to the 95% export pass-through

Second, I studied the effects of credit constraints on importers' exchange rate pass-through. I first use US measures of sectors’ financial vulnerability from Manova, Wei, and Zhang (2015) by matching the CIC industry codes to the ISIC system. Then we construct measures of credit needs based on Chinese information following Fan, Lai, Li (2015). From our baseline results, the import ERPT is higher for firms in more financial vulnerable industries. That is to say, import prices in sectors with large financial constraints are more sensitive to exchange rate shocks.

Third, I tried to study the channels under which credit constraints may affect the import pass-through. We started by checking firm's markup and total factor productivity (TFP). We estimated the firm-level markup and productivities following Loecker and Warzynski (2012) and Brooks, Kaboski, and Li (2021). Importers with higher TFP will have more complete import pass-through, while the markup levels do not have robust implications for pass-through. Exporters with higher TFP or higher markup levels will have lower pass-through. Credit constraints will still affect import pass-through if we control both markup or TFP.

### Future Plan

Our future plan is to further study the underlying mechanism of the import price responses to exchange rate shocks. We will look at factors that influence the bargaining power of Chinese firms in the global markets. Besides, we will also examine whether firms change the product quality in response to exchange rate shocks, such as importing low-quality intermediate products when the local currency depreciates. We will also use alternative measures of credit constraints as robustness checks and use instrumental variables to deal with potential endogenity issues.

Finally, we would like to further discuss the time trend of China's import exchange in recent years. Ideally, we would like to be able to distinguish the contribution of each factor to the trend in import exchange rate pass-through.

## 2022/05/25

Following the modified specifications with lagged markup and TFP controls and cross terms for import ERPT:
$$
\Delta \ln p_{IM;fpct}=[\alpha+\beta \cdot FinVuln_{f}+\gamma \cdot Markup_{ft-1}]*\Delta \ln RER_{ct}
+b \cdot \Delta \ln RGDP_{ct} \\ +c_1 \cdot MarketShare_{ft}+ c_2 \cdot Markup_{ft-1}+c_3 \cdot TFP_{ft-1}+\xi_{fpc}+\tau_{t} +\varepsilon_{fpct}
$$

$$
\Delta \ln p_{IM;fpct}=[\alpha+\beta \cdot FinVuln_{f}+\gamma \cdot TFP_{ft-1}]*\Delta \ln RER_{ct}
+b \cdot \Delta \ln RGDP_{ct} \\+c_1 \cdot MarketShare_{ft}+ c_2 \cdot Markup_{ft-1}+c_3 \cdot TFP_{ft-1}+\xi_{fpc}+\tau_{t} +\varepsilon_{fpct}
$$

We have results as below:

| | (1) | (2) | (3) | (4) | (5) | (6) |
| ----------------------- | ----------- | ----------- | ----------- | ----------- | ----------- | ----------- |
| | dlnprice_tr | dlnprice_tr | dlnprice_tr | dlnprice_tr | dlnprice_tr | dlnprice_tr |
| dlnRER | 0.142** | 0.090 | 0.332*** | 0.376*** | 0.342*** | 0.542*** |
| | (0.057) | (0.057) | (0.064) | (0.015) | (0.016) | (0.035) |
| dlnrgdp | 0.369*** | 0.381*** | 0.370*** | 0.389*** | 0.396*** | 0.389*** |
| | (0.086) | (0.086) | (0.086) | (0.086) | (0.086) | (0.086) |
| x_Markup_lag | 0.157*** | 0.167*** | 0.161*** | | | |
| | (0.042) | (0.042) | (0.042) | | | |
| x_tfp_lag | | | | 0.719*** | 0.656*** | 0.700*** |
| | | | | (0.056) | (0.056) | (0.056) |
| x_ExtFin_US | | 0.304*** | | | 0.246*** | |
| | | (0.032) | | | (0.032) | |
| x_Tang_US | | | -0.787*** | | | -0.674*** |
| | | | (0.126) | | | (0.127) |
| MS | -0.071*** | -0.071*** | -0.071*** | -0.070*** | -0.070*** | -0.070*** |
| | (0.008) | (0.008) | (0.008) | (0.008) | (0.008) | (0.008) |
| Markup_lag | 0.216*** | 0.213*** | 0.214*** | 0.213*** | 0.211*** | 0.211*** |
| | (0.012) | (0.012) | (0.012) | (0.012) | (0.012) | (0.012) |
| tfp_lag | -0.346*** | -0.341*** | -0.342*** | -0.340*** | -0.336*** | -0.337*** |
| | (0.016) | (0.016) | (0.016) | (0.016) | (0.016) | (0.016) |
| Year FE | Yes | Yes | Yes | Yes | Yes | Yes |
| Firm-product-country FE | Yes | Yes | Yes | Yes | Yes | Yes |
| N | 1297276 | 1297276 | 1297276 | 1297276 | 1297276 | 1297276 |

## 2022/05/31

For export ERPT, we also add lagged markup and TFP controls and cross terms:
$$
\Delta \ln p_{EX;fpct}=[\alpha+\beta \cdot FinVuln_{f}+\gamma \cdot Markup_{ft-1}]*\Delta \ln RER_{ct}
+b \cdot \Delta \ln RGDP_{ct} \\ +c_1 \cdot MarketShare_{ft}+ c_2 \cdot Markup_{ft-1}+c_3 \cdot TFP_{ft-1}+\xi_{fpc}+\tau_{t} +\varepsilon_{fpct}
$$

$$
\Delta \ln p_{EX;fpct}=[\alpha+\beta \cdot FinVuln_{f}+\gamma \cdot TFP_{ft-1}]*\Delta \ln RER_{ct}
+b \cdot \Delta \ln RGDP_{ct} \\+c_1 \cdot MarketShare_{ft}+ c_2 \cdot Markup_{ft-1}+c_3 \cdot TFP_{ft-1}+\xi_{fpc}+\tau_{t} +\varepsilon_{fpct}
$$

| | (1) | (2) | (3) | (4) | (5) | (6) |
| ----------------------- | ----------- | ----------- | ----------- | ----------- | ----------- | ----------- |
| | dlnprice_tr | dlnprice_tr | dlnprice_tr | dlnprice_tr | dlnprice_tr | dlnprice_tr |
| dlnRER | 0.003 | 0.005 | -0.023 | 0.029*** | 0.032*** | 0.002 |
| | (0.025) | (0.025) | (0.028) | (0.005) | (0.005) | (0.014) |
| dlnrgdp | -0.045 | -0.045 | -0.046 | -0.045 | -0.045 | -0.045 |
| | (0.032) | (0.032) | (0.032) | (0.032) | (0.032) | (0.032) |
| x_Markup_lag | 0.017 | 0.018 | 0.017 | | | |
| | (0.019) | (0.019) | (0.019) | | | |
| x_tfp_lag | | | | 0.042* | 0.051** | 0.043* |
| | | | | (0.023) | (0.024) | (0.023) |
| x_ExtFin_US | | -0.032** | | | -0.036*** | |
| | | (0.013) | | | (0.013) | |
| x_Tang_US | | | 0.100** | | | 0.104** |
| | | | (0.050) | | | (0.050) |
| MS | 0.014*** | 0.014*** | 0.014*** | 0.014*** | 0.014*** | 0.014*** |
| | (0.002) | (0.002) | (0.002) | (0.002) | (0.002) | (0.002) |
| Markup_lag | -0.003 | -0.003 | -0.003 | -0.002 | -0.002 | -0.002 |
| | (0.006) | (0.006) | (0.006) | (0.006) | (0.006) | (0.006) |
| tfp_lag | -0.026*** | -0.026*** | -0.026*** | -0.028*** | -0.029*** | -0.028*** |
| | (0.007) | (0.007) | (0.007) | (0.008) | (0.008) | (0.008) |
| Year FE | Yes | Yes | Yes | Yes | Yes | Yes |
| Firm-product-country FE | Yes | Yes | Yes | Yes | Yes | Yes |
| N | 1320527 | 1320527 | 1320527 | 1320527 | 1320527 | 1320527 |

## 2022/06/01

Three key findings of our project:

1. Import exchange rate pass-through is less complete than export exchange rate pass-through
2. Financial constraints will increase both import and export exchange rate pass-through to be more complete
3. The effect of financial constraints on exchange rate pass-through is robust and significant for both exporters and importers, which means the financial constraint factors work other than through the markup channel.