Abstract
We develop a dynamic general equilibrium model to explain the impact of environmental regulation, in a form of pollution tax, on the current account. The model predicts that the impact of pollution tax on the current account-total output ratio depends on the elasticity of pollution emission intensity in tradable sector to pollution tax and net foreign asset in the preceding period. When the elasticity exceeds the adjusted pollution tax expenditure-total output after tax ratio but is smaller than 1 and net foreign asset in the preceding period is positive, lower pollution tax and consequently more pollution emissions tend to decrease the trade balance-total output ratio and the current account-total output ratio; Otherwise, the impact would change with the above two conditions. Empirical evidence from 156 economies (1980–2018) shows a statistically and economically significant negative impact of pollution emissions on the current account-total output ratio when the preceding period’s net foreign asset is positive. The impact, however, is positive but statistically insignificant when the preceding period’s net foreign asset is negative. On the other hand, environmental regulation proxied by carbon tax has a significant negative impact on pollution emissions. It also poses a significant positive impact on the trade balance-total output ratio and the current account-total output ratio. Finally, we also find that the negative impact of pollution emissions on the current account-total output ratio is channeled by the real exchange rate appreciation caused by lower pollution tax.
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Notes
To the best of our knowledge, Holladay et al, (2019) is the only exception. However, one of the drawbacks of Holladay et al, (2019) is that they do not empirically determine the causal relationship between environmental regulation and the current account, for they do not use panel data for empirical analysis. Additionally, Holladay et al, (2019) mainly analyzes the current account balance in response to productivity and import price shocks in an RBC model incorporating environmental regulations. They fail to focus on the effect of environmental regulations and pollution emissions on the current account.
There are three main differences between our paper and Holladay et al, (2019). First, our model assumes a tradable vs. nontradable two-sector economy where tradables are pollution intensive and nontradable sector hardly produces pollutions. Holladay et al, (2019), however, assumes a one-sector economy (an economy in which all goods are tradable). It is worth pointing out that using a two-sector approach, our model allows the real exchange rate (relative price of nontradables to tradables) to play an important role in explaining the behavior of some key variables, such as consumption of tradables, total output, trade balance and the current account as well. The real exchange rate is also a mechanism through which environmental regulation affects the current account, which is the primary interest of the paper. But Holladay et al, (2019) fails to take the real exchange rate into account when exploring the impact of environmental regulation on the current account. Second, we focus on the effect of pollution tax on the current account using a dynamic general equilibrium model, while Holladay et al, (2019) focuses on the change of macro variables such as total output and trade balance in response to exogenous TFP and import price shocks using an RBC model. Third, we use panel data of 156 economies to test the causal relationship between environmental regulation and the current account, while Holladay et al, (2019) uses data of Canada to calibrate the model. To sum up, both theoretical contribution and empirical analysis of our paper are different from Holladay et al, (2019).
Pollution emission intensity is pollution emissions per output. For detailed discussions, see subsection 3.3.2 on pages 8 and 9.
Our model assumes that tradables are more pollution intensive than nontradables, as supported by the evidence from Copeland et al, (2021). One of the stylized facts confirmed by Copeland et al, (2021) is that dirty industries are more exposed to trade. They attribute this pattern to the fact that manufacturing industries are relatively dirty while services are cleaner and manufacturing goods are more often traded. In fact, in the industries summarized by Copeland et al, (2021), tradables (such as equipment and machine rentals, coke, oil refining and nuclear fuel, air transport, water transport and other non-metallic mineral) are more exposed to pollution while nontradables (such as real estate activities, financial intermediation, wholesale trade) are not.
Following Holladay et al, (2019), households are assumed to ignore the pollution emissions in their optimization decision. Therefore, pollutions do not appear in the utility function.
For first order conditions with respect to \({L}_{T,t}\) and \({L}_{N,t}\), see Appendix 1.
See Appendix 1 for simple proofs.
See Appendix 1 for a proof.
Using data of our sample in the following section, the estimated adjusted pollution tax expenditure-total output after tax ratio (\({\delta }_{3}\frac{{}_{t}{E}_{t}}{{Y}_{T,t}}\)) ranges from 0.034 to 0.110, depending on different classifications of tradable and nontradable sectors. We therefore hold that \(\left|\frac{{\text{dln}}\left({E}_{t}/{Y}_{T,t}\right)}{{\text{dln}}{\tau }_{t}}\right|\) is most likely to be larger than \({\delta }_{3}\frac{{}_{t}{E}_{t}}{{Y}_{T,t}}\). We consider four classification schemes when estimating the ratio. First, we classify agriculture and industry as tradable sector, while services as nontradable sector (Ricci et al., 2013). Second, we view industry as tradable sector, and the rest as nontradable sector. Third, tradable sector includes agriculture and manufacturing, while nontradable sector includes services and industry excluding manufacturing. Fourth, we classify manufacturing only as tradable sector, and the rest as nontradable sector. Data of pollution tax expenditure-GDP ratio (\(\frac{{}_{t}{E}_{t}}{{Y}_{T,t}+{q}_{t}{Y}_{N,t}}\)) comes from the OECD. Data on output of agriculture, industry, manufacturing and services comes from the WDI. Due to data availability of the OECD, only 110 economies in our total sample (156 economies) are used to estimate \({\delta }_{3}\frac{{}_{t}{E}_{t}}{{Y}_{T,t}}\).
Table A-1 in the Appendix 2 summarizes the Proposition.
For convenience, we sometimes use pollution emission intensity interchangeably since both terms are equivalently the same.
The choice of sample economies has been made on the basis of data availability.
It is possible that the average current account-GDP ratio across the sample is not zero in a given year. First, although theoretically, the sum of (and thus the average) current account (CA) of all countries in the world should always be zero, it has long been noticed that CA of all countries do not sum up to zero, known as the ‘‘global CA discrepancy” (Beckmann et al., 2022). Second, note that the indicator in Fig. 1 is the average current account-GDP ratio rather than the average level of the current account across economies. Third, the sample covers only 156 economies rather than the whole world.
Considering that CO2 emission intensity may be affected by a variety of factors such as technology shifts, inflation, business cycles and so on, we include total factor productivity (tfp, Bloom et al., 2016), inflation (inf, Chinn and Prasad., 2003), and real GDP growth rate (rgdpg, Hansen and Wagner., 2022), as proxies for the three potential factors into regressions of pollution emission intensity (pe) on carbon tax (ct) and rerun regressions in columns (1), (4) and (7) in Table 3. The results in Table A-5 show that pollution emission intensity is still negatively influenced by carbon tax.
We further include total factor productivity (tfp), inflation (inf), and real GDP growth rate (rgdpg) into the (baseline) regressions of the current account (ca) on pollution emission intensity (pe) (columns (1), (3) and (5) in Table A-6). We fail to find evidence against our baseline results.
In addition, we use the residual in the regression of pe (pollution emissions) on the tfp (total factor productivity), inf (inflation), rgdpg (real GDP growth) and other control variables as the independent variable to rerun the regressions in columns (1), (3) and (5) of Table A-6. The independent variable represents pollution emissions excluding the effect of technology shifts, inflation, business cycles and other factors. It is more likely to be affected mainly by environmental regulations. The results in columns (2), (4) and (6) shows that the coefficients of the independent variable are the same as those in columns (1), (3) and (5) respectively.
Twenty-five economies all over the world have carbon tax policies in implementation by 2020. Among the 25 economies, two implemented carbon tax policy in 2019, and carbon tax data in another economy (Liechtenstein) is not available (For detailed information, refer to https://ourworldindata.org/carbon-pricing). Therefore, only 22 economies in our sample have carbon tax data. Besides, only 6 economies have data on carbon tax before 2000, among which Finland and Poland were the first two to levy carbon tax policy in 1990. Therefore, data on carbon tax in more than 85% economies in the total sample (156 economies) is unavailable.
It is also worth pointing out that in regressions here, if an economy does not have carbon tax in place in a certain year, carbon tax (ct) in that year is set to zero (as presented in Our World in Data). Otherwise, carbon tax (ct) equals to the tax rate levied.
Some recent studies also provide more empirical evidence and mechanisms on the negative relation between CO2 emission from, say, industrial or steel productions with precipitation (Kotz et al., 2022; Wu et al., 2023). Kotz et al, (2022) and Liang, (2022)) show that manufacturing sectors are worse off than agricultural sector in wet days and excessive precipitation. The mechanisms that industrial production is negatively affected by precipitation include lower wages per capita, lower labor productivity, higher inventory, higher depreciation and lower capital productivity (Wu et al., 2023). First, heavy precipitation will increase traffic jams and accidents. This in turn results in more commuting time or absenteeism and thus fewer overall working hours. Consequently, wages per capita decrease. Second, heavy precipitation will decrease labor productivity due to workers’ terrible mood and performance caused by travel inconveniences and high humidity. Third, increased transportation cost and even traffic paralysis will cause higher inventory. Fourth, heavy precipitation will lead to higher depreciation due to higher failure rate of machines. Finally, heavy precipitation will cause a decline in capital productivity due to damage to factories with substandard construction and machines.
This is the so-called Environmental Kuznets Curve.
Data of the first four variables comes from World Development Indicators (WDI). Data of natural disasters (dis) comes from the international disasters database.
We admit that we are unable to definitely rule out all the possibility of the effect that precipitation could have on the current account, either directly or indirectly, beyond its impact working through pollution emissions. Nevertheless, we believe that these other potential effects are likely to be minor and unlikely to pose significant impacts on our main conclusions.
There are two reasons why we do not include the real exchange rate as a control variable in our baseline regressions and robustness checks. First, the real exchange rate acts as an intermediary channel in our paper, to mediate the impact of pollution emissions on the current account. Second, although the real exchange rate affects the current account unilaterally in our model, it is possible that the current account will in turn influence the real exchange rate in practice. This means the real exchange rate is an endogenous variable once included in the regressions. This will result in the potential endogeneity problem. There will be bias not only in the coefficient estimate of the real exchange rate itself, but also in that of other variables including the explanatory variable.
References
Afonso, A., Huart, F., Jalles, J. T., & Stanek, P. (2022). Twin deficits revisited: A role for fiscal institutions? Journal of International Money and Finance, 121, 102506.
Antweiler, W., Copeland, B. R., & Taylor, M. S. (2001). Is free trade good for the environment? American Economic Review, 91(4), 877–908.
Asea, P. K., & Corden, W. M. (1994). The Balassa-Samuelson model: An overview. Review of International Economics, 2, 191–200.
Beckmann, J., Belke, A., & Gros, D. (2022). Savings-investment and the current account: More measurement than identity. Journal of International Money and Finance, 121, 102507.
Bloom, N., Draca, M., & Van Reenen, J. (2016). Trade induced technical change? The impact of chinese imports on innovation, IT and productivity. Review of Economic Studies, 83(1), 87–117.
Cardi, O., & Restout, R. (2015). Imperfect mobility of labor across sectors: A reappraisal of the Balassa-Samuelson effect. Journal of International Economics, 97(2), 249–265.
Cherniwchan, J., & Najjar, N. (2022). Do environmental regulations affect the decision to export? American Economic Journal: Economic Policy, 14(2), 125–160.
Chinn, M. D., & Ito, H. (2006). What matters for financial development? Capital controls, institutions, and interactions. Journal of Development Economics, 81(1), 163–192.
Chinn, M. D., & Ito, H. (2007). Current account balances, financial development and institutions: Assaying the world saving glut. Journal of International Money and Finance, 26(4), 546–569.
Chinn, M. D., & Ito, H. (2022). A requiem for “blame it on Beijing”: Interpreting rotating global current account surpluses. Journal of International Money and Finance, 121, 102510.
Chinn, M. D., & Prasad, E. S. (2003). Medium-term determinants of current accounts in industrial and lower-income countries: An empirical exploration. Journal of International Economics, 59(1), 47–76.
Copeland, B. R., Shapiro, J. S., & Taylor, M. S. (2021). Globalization and the environment (Working paper 28797). National Bureau of Economic Research.
Copeland, B. R., & Taylor, M. S. (2003). Trade and the environment: Theory and evidence. Princeton University Press.
Copeland, B. R., & Taylor, M. S. (2004). Trade, growth, and the environment. Journal of Economic Literature, 42(1), 7–71.
Costantini, V., & Crespi, F. (2008). Environmental regulation and the export dynamics of energy technologies. Ecological Economics, 66(2–3), 447–460.
Coulibaly, D., Gnimassoun, B., & Mignon, V. (2020). The tale of two international phenomena: Migration and global imbalances. Journal of Macroeconomics, 66, 103241.
De Gregorio, J., Giovannini, A., & Wolf, H. C. (1994). International evidence on tradables and nontradable inflation. European Economic Review, 38(6), 1225–1244.
De Gregorio, J., & Wolf, H. C. (1994). Terms of trade, productivity and the real exchange rate (Working paper 4807). National Bureau of Economic Research.
Dell, M., Jones, B. F., & Olken, B. A. (2014). What do we learn from the weather? The new climate-economy literature. Journal of Economic Literature, 52(3), 740–798.
Duan, Y., Ji, T., Lu, Y., & Wang, S. (2021). Environmental regulations and international trade: A quantitative economic analysis of world pollution emissions. Journal of Public Economics, 203, 1–37.
Dumrongrittikul, T., & Anderson, H. M. (2016). How do shocks to domestic factors affect real exchange rates of Asian lower-income countries? Journal of Development Economics, 119(3), 67–85.
Feenstra, R. C., Inklaar, R., & Timmer, M. (2015). The next generation of the penn world table. American Economic Review, 105(10), 3150–3182.
Fishback, P., Horrace, W. C., & Kantor, S. (2006). The impact of new deal expenditures on mobility during the great depression. Explorations in Economic History, 43(2), 179–222.
Fontenla, M., Goodwin, M. B., & Gonzalez, F. (2019). Pollution and the choice of where to work and live within Mexico City. Latin American Economic Review, 28(1), 1–17.
Gazze, L., Persico, C., & Spirovska, S. (2021). The long-run spillover effects of pollution: How exposure to lead affects everyone in the classroom (Working paper 28782). National Bureau of Economic Research.
Gray, W. B., & Shadbegian, R. J. (2003). Plant vintage, technology, and environmental regulation. Journal of Environmental Economics and Management, 46(3), 384–402.
Hansen, E., & Wagner, R. (2022). The reinvestment by multinationals as a capital flow: Crises, imbalances, and the cash-based current account. Journal of International Money and Finance, 124, 1–19.
Hering, L., & Poncet, S. (2014). Environmental policy and exports: Evidence from Chinese cities. Journal of Environmental Economics and Management, 68(2), 296–318.
Holladay, J. S., Mohsin, M., & Pradhan, S. (2019). Environmental policy instrument choice and international trade. Environmental and Resource Economics, 74(4), 1585–1617.
Jones, B. F., & Olken, B. A. (2010). Climate shocks and exports. American Economic Review, 100(2), 454–459.
Jug, J., & Mirza, D. (2005). Environmental regulations in gravity equations: Evidence from Europe. World Economy, 28(11), 1591–1615.
Kang, Y., & Liu, X. (2019). Firm heterogeneity in the tradable sector, export product diversification and real exchange rate. The Journal of World Economy, 12, 166–188.
Kotz, M., Levermann, A., & Wenz, L. (2022). The effect of rainfall changes on economic production. Nature, 601(7892), 223–227.
Kuziemska-Pawlak, K., & Mućk, J. (2020). Structural current accounts in the European Union countries: Cross-sectional exploration. Economic Modelling, 93, 445–464.
Lanoie, P., Patry, M., & Lajeunesse, R. (2008). Environmental regulation and productivity: Testing the Porter hypothesis. Journal of Productivity Analysis, 30(2), 121–128.
Levinson, A., & Taylor, M. S. (2008). Unmasking the pollution haven effect. International Economic Review, 49(1), 223–254.
Li, B., & Ren, Y. (2015). How does demographic structure affect current account imbalance? Empirical evidence from the instrumental variable estimation of WWII. Economic Research Journal, 10, 119–133.
Liang, X. Z. (2022). Extreme rainfall slows the global economy. Nature, 601(7892), 193–194.
List, J. A., McHone, W. W., & Millimet, D. L. (2004). Effects of environmental regulation on foreign and domestic plant births: Is there a home field advantage? Journal of Urban Economics, 56(2), 303–326.
Liu, M., Tan, R., & Zhang, B. (2021a). The costs of “blue sky”: Environmental regulation, technology upgrading, and labor demand in China. Journal of Development Economics, 150, 1–16.
Liu, X., Ren, J., & Zhang, J. (2021b). A century review on current account: Balances versus temporary and sustained imbalances. Economic Review, 2, 149–162.
López-Córdova, E. (2005). Globalization, migration, and development: The role of Mexican migrant remittances. Economia, 6(1), 217–256.
Miguel, E., Satyanath, S., & Sergenti, E. (2004). Economic shocks and civil conflict: An instrumental variables approach. Journal of Political Economy, 112(4), 725–753.
Obstfeld, M. (2012). Does the current account still matter? American Economic Review, 102(3), 1–23.
Peet, E. D. (2021). Early-life environment and human capital: Evidence from the Philippines. Environment and Development Economics, 26(1), 1–25.
Persico, C., Figlio, D., & Roth, J. (2020). The developmental consequences of superfund sites. Journal of Labor Economics, 38(4), 1055–1097.
Ricci, L. A., Milesi-Ferretti, G. M., & Lee, J. (2013). Real exchange rates and fundamentals: A cross-country perspective. Journal of Money, Credit and Banking, 45(5), 845–865.
Rogoff, K. (1992). Traded goods consumption smoothing and the random walk behavior of the real exchange rate (Working paper w4119). National Bureau of Economic Research.
Rose, A. K., Supaat, S., & Braude, J. (2009). Fertility and the real exchange rate. Canadian Journal of Economics, 42, 496–518.
Shi, X., & Xu, Z. (2018). Environmental regulation and firm exports: Evidence from the eleventh five-year plan in China. Journal of Environmental Economics and Management, 89(3), 187–200.
Svensson, L. E. O., & Razin, A. (1983). The terms of trade and the current account: The Harberger-Laursen-Metzler effect. Journal of Political Economy, 91(1), 97–125.
Tan, Z., & Zhao, Y. (2012). Bank concentration, corporate savings and current account imbalances. Economic Research Journal, 12, 55–68.
Tong, J., Yun, W., & Peng, Z. (2011). New international division, global imbalances and financial innovation. Nankai Economic Studies, 3, 3–15.
Wu, H., Guo, H., Zhang, B., & Bu, M. (2017). Westward movement of new polluting firms in China: Pollution reduction mandates and location choice. Journal of Comparative Economics, 45(1), 119–138.
Wu, Z., Zhou, T., Zhang, N., Choi, Y., & Kong, F. (2023). A hidden risk in climate change: The effect of daily rainfall shocks on industrial activities. Economic Analysis and Policy, 80, 161–180.
Xu, J., & Yao, Y. (2010). The new international division of labor, financial integration, and global imbalances. The Journal of World Economy, 3, 3–30.
Yang, C. H., Tseng, Y. H., & Chen, C. P. (2012). Environmental regulations, induced R&D, and productivity: Evidence from Taiwan’s manufacturing industries. Resource and Energy Economics, 34(4), 514–532.
Zhai, X., & Liu, W. (2012). Cointegration analysis of influencing factors of China’s current account surplus from the perspective of residents’ consumption ability. Journal of Finance and Economics, 3, 26–36.
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We are grateful for constructive and insightful suggestions from two anonymous reviewees and the editor. However, all the errors are our responsibilities.
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The paper is financially supported by the National Social Science Fund of China (23&ZD059; 19BJL131), and National Natural Science Foundation of China (71973109).
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Zheng, S., Liu, X. & Zuo, Y. Environmental regulation, pollution emissions and the current account. Rev World Econ (2024). https://doi.org/10.1007/s10290-024-00530-y
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DOI: https://doi.org/10.1007/s10290-024-00530-y