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28512 | Trade jobs and wages | untitled-reusable-block-165 | wp_block | publish | <!-- wp:heading {"level":4} --> <h4>Evidence from Chinese imports and their impact on factory workers in the US</h4> <!-- /wp:heading --> <!-- wp:paragraph --> <p>The most famous study looking at this question is Autor, Dorn and Hanson (2013): "The China syndrome: Local labor market effects of import competition in the United States".{ref}David, H., Dorn, D., & Hanson, G. H. (2013). The China syndrome: Local labor market effects of import competition in the United States. American Economic Review, 103(6), 2121-68. Available online here: <a rel="noreferrer noopener" href="http://economics.mit.edu/files/7723" target="_blank">http://economics.mit.edu/files/7723</a>{/ref}</p> <!-- /wp:paragraph --> <!-- wp:paragraph --> <p>In this paper, Autor and coauthors looked at how local labor markets changed in the parts of the country most exposed to Chinese competition, and they found that rising exposure increased unemployment, lowered labor force participation, and reduced wages. Additionally, they found that claims for unemployment and healthcare benefits also increased in more trade-exposed labor markets.</p> <!-- /wp:paragraph --> <!-- wp:paragraph --> <p>The visualization here is one of the key charts from their paper. It's a scatter plot of cross-regional exposure to rising imports, against changes in employment. Each dot is a small region (a 'commuting zone' to be precise). The vertical position of the dots represents the percent change in manufacturing employment for working age population; and the horizontal position represents the predicted exposure to rising imports (exposure varies across regions depending on the local weight of different industries).</p> <!-- /wp:paragraph --> <!-- wp:paragraph --> <p>The trend line in this chart shows a negative relationship: more exposure goes together with less employment. There are large deviations from the trend (there are some low-exposure regions with big negative changes in employment); but the paper provides more sophisticated regressions and robustness checks, and finds that this relationship is statistically significant.</p> <!-- /wp:paragraph --> <!-- wp:heading {"level":6} --> <h6>Exposure to rising Chinese imports and changes in employment across local labor markets in the US (1999-2007) – Autor, Dorn and Hanson (2013)</h6> <!-- /wp:heading --> <!-- wp:image {"align":"center","id":21012,"linkDestination":"custom"} --> <div class="wp-block-image"><figure class="aligncenter"><a href="https://owid.cloud/app/uploads/2018/09/Autor-et-al-Fig-2b-01.png"><img src="https://owid.cloud/app/uploads/2018/09/Autor-et-al-Fig-2b-01-721x550.png" alt="" class="wp-image-21012"/></a></figure></div> <!-- /wp:image --> <!-- wp:paragraph --> <p>This result is important because it shows that the labor market adjustments were large. Many workers and communities were affected over a long period of time.{ref}It's important to mention here that the economist Jonathan Rothwell recently wrote a <a rel="noreferrer noopener" href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2920188" target="_blank">paper</a> suggesting these findings are the result of a statistical illusion. Rothwell's critique received some <a rel="noreferrer noopener" href="https://www.wsj.com/articles/the-truth-about-the-china-trade-shock-1491168339" target="_blank">attention from the media</a>, but Autor and coauthors provided a <a rel="noreferrer noopener" href="http://economics.mit.edu/files/12729" target="_blank">reply</a>, which I think successfully refutes this claim. {/ref}</p> <!-- /wp:paragraph --> <!-- wp:paragraph --> <p>But it's also important to keep in mind that Autor and colleagues are only giving us a partial perspective on the total effect of trade on employment. In particular, comparing changes in employment at the regional level misses the fact that firms operate in multiple regions and industries at the same time. Indeed, <a rel="noopener noreferrer" href="http://www.columbia.edu/~im2348/JMP_Magyari.pdf" target="_blank">Ildikó Magyari recently found evidence</a> suggesting the Chinese trade shock provided incentives for US firms to diversify and reorganize production.{ref}Magyari, I. (2017). Firm Reorganization, Chinese Imports, and US Manufacturing Employment. US Census Bureau, Center for Economic Studies. Available online <a rel="noreferrer noopener" href="http://www.columbia.edu/~im2348/JMP_Magyari.pdf" target="_blank">here</a>.{/ref}</p> <!-- /wp:paragraph --> <!-- wp:paragraph --> <p> So companies that outsourced jobs to China often ended up closing some lines of business, but at the same time expanded other lines elsewhere in the US. This means that job losses in some regions subsidized new jobs in other parts of the country.</p> <!-- /wp:paragraph --> <!-- wp:paragraph --> <p>On the whole, Magyari finds that although Chinese imports may have reduced employment within some establishments, these losses were more than offset by gains in employment within the same firms in other places. This is no consolation to people who lost their job. But it is necessary to add this perspective to the simplistic story of "trade with China is bad for US workers".</p> <!-- /wp:paragraph --> <!-- wp:heading {"level":4} --> <h4>Evidence from the expansion of trade in India and the impact on poverty reductions</h4> <!-- /wp:heading --> <!-- wp:paragraph --> <p>Another important paper in this field is Topalova (2010): "Factor immobility and regional impacts of trade liberalization: Evidence on poverty from India".{ref}Topalova, P. (2010). Factor immobility and regional impacts of trade liberalization: Evidence on poverty from India. American Economic Journal: Applied Economics, 2(4), 1-41. Available online <a rel="noreferrer noopener" href="http://dl.kli.re.kr/dl_image/IMG/03/000000012162/SERVICE/000000012162_01.PDF" target="_blank">here</a>.{/ref}</p> <!-- /wp:paragraph --> <!-- wp:paragraph --> <p>In this paper Topalova looks at the impact of trade liberalization on poverty across different regions in India, using the sudden and extensive <a href="https://ourworldindata.org/grapher/trade-as-share-of-gdp?country=IND">change</a> in India's trade policy in 1991. She finds that rural regions that were more exposed to liberalization, experienced a slower decline in poverty, and had lower consumption growth.</p> <!-- /wp:paragraph --> <!-- wp:paragraph --> <p>In the analysis of the mechanisms underlying this effect, Topalova finds that liberalization had a stronger negative impact among the least geographically mobile at the bottom of the income distribution, and in places where labor laws deterred workers from reallocating across sectors.</p> <!-- /wp:paragraph --> <!-- wp:paragraph --> <p>The evidence from India shows that (i) discussions that only look at "winners" in poor countries and "losers" in rich countries miss the point that the gains from trade are unequally distributed within both sets of countries; and (ii) context-specific factors, like worker mobility across sectors and geographic regions, are crucial to understand the impact of trade on incomes.</p> <!-- /wp:paragraph --> <!-- wp:heading {"level":4} --> <h4>Evidence from other studies</h4> <!-- /wp:heading --> <!-- wp:list --> <ul><li>Donaldson (2018) uses archival data from colonial India to estimate the impact of India’s vast railroad network. He finds railroads increased trade, and in doing so they increased real incomes (and reduced income volatility).{ref}Donaldson, D. (2018). Railroads of the Raj: Estimating the impact of transportation infrastructure. American Economic Review, 108(4-5), 899-934. Available online <a rel="noreferrer noopener" href="http://eprints.lse.ac.uk/38368/1/ARCWP41-Donaldson.pdf" target="_blank">here</a>.{/ref}</li><li> Porto (2006) looks at the distributional effects of <a rel="noreferrer noopener" href="https://en.wikipedia.org/wiki/Mercosur" target="_blank">Mercosur</a> on Argentine families, and finds this regional trade agreement led to benefits across the entire income distribution. He finds the effect was progressive: poor households gained more than middle-income households, because prior to the reform, trade protection benefitted the rich disproportionately.{ref}Porto, G (2006). Using Survey Data to Assess the Distributional Effects of Trade Policy. Journal of International Economics 70 (2006) 140–160.{/ref}</li><li>Trefler (2004) looks at the Canada-US Free Trade Agreement and finds there was a group who bore "adjustment costs" (displaced workers and struggling plants) and a group who enjoyed "long-run gains" (consumers and efficient plants). {ref}Trefler, D. (2004). The long and short of the Canada-US free trade agreement. American Economic Review, 94(4), 870-895. Available online <a rel="noreferrer noopener" href="https://www.aeaweb.org/articles?id=10.1257/0002828042002633" target="_blank">here</a>.{/ref}</li></ul> <!-- /wp:list --> | { "id": "wp-28512", "slug": "untitled-reusable-block-165", "content": { "toc": [], "body": [ { "text": [ { "text": "Evidence from Chinese imports and their impact on factory workers in the US", "spanType": "span-simple-text" } ], "type": "heading", "level": 2, "parseErrors": [] }, { "type": "text", "value": [ { "text": "The most famous study looking at this question is Autor, Dorn and Hanson (2013): \"The China syndrome: Local labor market effects of import competition in the United States\".{ref}David, H., Dorn, D., & Hanson, G. H. (2013). The China syndrome: Local labor market effects of import competition in the United States. American Economic Review, 103(6), 2121-68. 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2019-11-25 20:43:51 | 2024-02-16 14:22:59 | [ null ] |
2019-11-25 20:44:05 | 2020-04-30 14:00:12 | {} |
## Evidence from Chinese imports and their impact on factory workers in the US The most famous study looking at this question is Autor, Dorn and Hanson (2013): "The China syndrome: Local labor market effects of import competition in the United States".{ref}David, H., Dorn, D., & Hanson, G. H. (2013). The China syndrome: Local labor market effects of import competition in the United States. American Economic Review, 103(6), 2121-68. Available online here: [http://economics.mit.edu/files/7723](http://economics.mit.edu/files/7723){/ref} In this paper, Autor and coauthors looked at how local labor markets changed in the parts of the country most exposed to Chinese competition, and they found that rising exposure increased unemployment, lowered labor force participation, and reduced wages. Additionally, they found that claims for unemployment and healthcare benefits also increased in more trade-exposed labor markets. The visualization here is one of the key charts from their paper. It's a scatter plot of cross-regional exposure to rising imports, against changes in employment. Each dot is a small region (a 'commuting zone' to be precise). The vertical position of the dots represents the percent change in manufacturing employment for working age population; and the horizontal position represents the predicted exposure to rising imports (exposure varies across regions depending on the local weight of different industries). The trend line in this chart shows a negative relationship: more exposure goes together with less employment. There are large deviations from the trend (there are some low-exposure regions with big negative changes in employment); but the paper provides more sophisticated regressions and robustness checks, and finds that this relationship is statistically significant. #### Exposure to rising Chinese imports and changes in employment across local labor markets in the US (1999-2007) – Autor, Dorn and Hanson (2013) <Image filename="Autor-et-al-Fig-2b-01.png" alt=""/> This result is important because it shows that the labor market adjustments were large. Many workers and communities were affected over a long period of time.{ref}It's important to mention here that the economist Jonathan Rothwell recently wrote a [paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2920188) suggesting these findings are the result of a statistical illusion. Rothwell's critique received some [attention from the media](https://www.wsj.com/articles/the-truth-about-the-china-trade-shock-1491168339), but Autor and coauthors provided a [reply](http://economics.mit.edu/files/12729), which I think successfully refutes this claim. {/ref} But it's also important to keep in mind that Autor and colleagues are only giving us a partial perspective on the total effect of trade on employment. In particular, comparing changes in employment at the regional level misses the fact that firms operate in multiple regions and industries at the same time. Indeed, [Ildikó Magyari recently found evidence](http://www.columbia.edu/~im2348/JMP_Magyari.pdf) suggesting the Chinese trade shock provided incentives for US firms to diversify and reorganize production.{ref}Magyari, I. (2017). Firm Reorganization, Chinese Imports, and US Manufacturing Employment. US Census Bureau, Center for Economic Studies. Available online [here](http://www.columbia.edu/~im2348/JMP_Magyari.pdf).{/ref} So companies that outsourced jobs to China often ended up closing some lines of business, but at the same time expanded other lines elsewhere in the US. This means that job losses in some regions subsidized new jobs in other parts of the country. On the whole, Magyari finds that although Chinese imports may have reduced employment within some establishments, these losses were more than offset by gains in employment within the same firms in other places. This is no consolation to people who lost their job. But it is necessary to add this perspective to the simplistic story of "trade with China is bad for US workers". ## Evidence from the expansion of trade in India and the impact on poverty reductions Another important paper in this field is Topalova (2010): "Factor immobility and regional impacts of trade liberalization: Evidence on poverty from India".{ref}Topalova, P. (2010). Factor immobility and regional impacts of trade liberalization: Evidence on poverty from India. American Economic Journal: Applied Economics, 2(4), 1-41. Available online [here](http://dl.kli.re.kr/dl_image/IMG/03/000000012162/SERVICE/000000012162_01.PDF).{/ref} In this paper Topalova looks at the impact of trade liberalization on poverty across different regions in India, using the sudden and extensive [change](https://ourworldindata.org/grapher/trade-as-share-of-gdp?country=IND) in India's trade policy in 1991. She finds that rural regions that were more exposed to liberalization, experienced a slower decline in poverty, and had lower consumption growth. In the analysis of the mechanisms underlying this effect, Topalova finds that liberalization had a stronger negative impact among the least geographically mobile at the bottom of the income distribution, and in places where labor laws deterred workers from reallocating across sectors. The evidence from India shows that (i) discussions that only look at "winners" in poor countries and "losers" in rich countries miss the point that the gains from trade are unequally distributed within both sets of countries; and (ii) context-specific factors, like worker mobility across sectors and geographic regions, are crucial to understand the impact of trade on incomes. ## Evidence from other studies * Donaldson (2018) uses archival data from colonial India to estimate the impact of India’s vast railroad network. He finds railroads increased trade, and in doing so they increased real incomes (and reduced income volatility).{ref}Donaldson, D. (2018). Railroads of the Raj: Estimating the impact of transportation infrastructure. American Economic Review, 108(4-5), 899-934. Available online [here](http://eprints.lse.ac.uk/38368/1/ARCWP41-Donaldson.pdf).{/ref} * Porto (2006) looks at the distributional effects of [Mercosur](https://en.wikipedia.org/wiki/Mercosur) on Argentine families, and finds this regional trade agreement led to benefits across the entire income distribution. He finds the effect was progressive: poor households gained more than middle-income households, because prior to the reform, trade protection benefitted the rich disproportionately.{ref}Porto, G (2006). Using Survey Data to Assess the Distributional Effects of Trade Policy. Journal of International Economics 70 (2006) 140–160.{/ref} * Trefler (2004) looks at the Canada-US Free Trade Agreement and finds there was a group who bore "adjustment costs" (displaced workers and struggling plants) and a group who enjoyed "long-run gains" (consumers and efficient plants). {ref}Trefler, D. (2004). The long and short of the Canada-US free trade agreement. American Economic Review, 94(4), 870-895. Available online [here](https://www.aeaweb.org/articles?id=10.1257/0002828042002633).{/ref} | { "data": { "wpBlock": { "content": "\n<h4>Evidence from Chinese imports and their impact on factory workers in the US</h4>\n\n\n\n<p>The most famous study looking at this question is Autor, Dorn and Hanson (2013): “The China syndrome: Local labor market effects of import competition in the United States”.{ref}David, H., Dorn, D., & Hanson, G. H. (2013). The China syndrome: Local labor market effects of import competition in the United States. American Economic Review, 103(6), 2121-68. Available online here: <a rel=\"noreferrer noopener\" href=\"http://economics.mit.edu/files/7723\" target=\"_blank\">http://economics.mit.edu/files/7723</a>{/ref}</p>\n\n\n\n<p>In this paper, Autor and coauthors looked at how local labor markets changed in the parts of the country most exposed to Chinese competition, and they found that rising exposure increased unemployment, lowered labor force participation, and reduced wages. Additionally, they found that claims for unemployment and healthcare benefits also increased in more trade-exposed labor markets.</p>\n\n\n\n<p>The visualization here is one of the key charts from their paper. It’s a scatter plot of cross-regional exposure to rising imports, against changes in employment. Each dot is a small region (a ‘commuting zone’ to be precise). The vertical position of the dots represents the percent change in manufacturing employment for working age population; and the horizontal position represents the predicted exposure to rising imports (exposure varies across regions depending on the local weight of different industries).</p>\n\n\n\n<p>The trend line in this chart shows a negative relationship: more exposure goes together with less employment. There are large deviations from the trend (there are some low-exposure regions with big negative changes in employment); but the paper provides more sophisticated regressions and robustness checks, and finds that this relationship is statistically significant.</p>\n\n\n\n<h6>Exposure to rising Chinese imports and changes in employment across local labor markets in the US (1999-2007) \u2013 Autor, Dorn and Hanson (2013)</h6>\n\n\n\n<div class=\"wp-block-image\"><figure class=\"aligncenter\"><a href=\"https://owid.cloud/app/uploads/2018/09/Autor-et-al-Fig-2b-01.png\"><img loading=\"lazy\" width=\"721\" height=\"550\" src=\"https://owid.cloud/app/uploads/2018/09/Autor-et-al-Fig-2b-01-721x550.png\" alt=\"\" class=\"wp-image-21012\" srcset=\"https://owid.cloud/app/uploads/2018/09/Autor-et-al-Fig-2b-01-721x550.png 721w, https://owid.cloud/app/uploads/2018/09/Autor-et-al-Fig-2b-01-150x114.png 150w, https://owid.cloud/app/uploads/2018/09/Autor-et-al-Fig-2b-01-400x305.png 400w, https://owid.cloud/app/uploads/2018/09/Autor-et-al-Fig-2b-01-768x586.png 768w, https://owid.cloud/app/uploads/2018/09/Autor-et-al-Fig-2b-01.png 1209w\" sizes=\"(max-width: 721px) 100vw, 721px\" /></a></figure></div>\n\n\n\n<p>This result is important because it shows that the labor market adjustments were large. Many workers and communities were affected over a long period of time.{ref}It’s important to mention here that the economist Jonathan Rothwell recently wrote a <a rel=\"noreferrer noopener\" href=\"https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2920188\" target=\"_blank\">paper</a> suggesting these findings are the result of a statistical illusion. Rothwell’s critique received some <a rel=\"noreferrer noopener\" href=\"https://www.wsj.com/articles/the-truth-about-the-china-trade-shock-1491168339\" target=\"_blank\">attention from the media</a>, but Autor and coauthors provided a <a rel=\"noreferrer noopener\" href=\"http://economics.mit.edu/files/12729\" target=\"_blank\">reply</a>, which I think successfully refutes this claim. {/ref}</p>\n\n\n\n<p>But it’s also important to keep in mind that Autor and colleagues are only giving us a partial perspective on the total effect of trade on employment. In particular, comparing changes in employment at the regional level misses the fact that firms operate in multiple regions and industries at the same time. Indeed, <a rel=\"noopener noreferrer\" href=\"http://www.columbia.edu/~im2348/JMP_Magyari.pdf\" target=\"_blank\">Ildik\u00f3 Magyari recently found evidence</a> suggesting the Chinese trade shock provided incentives for US firms to diversify and reorganize production.{ref}Magyari, I. (2017). Firm Reorganization, Chinese Imports, and US Manufacturing Employment. US Census Bureau, Center for Economic Studies. Available online <a rel=\"noreferrer noopener\" href=\"http://www.columbia.edu/~im2348/JMP_Magyari.pdf\" target=\"_blank\">here</a>.{/ref}</p>\n\n\n\n<p> So companies that outsourced jobs to China often ended up closing some lines of business, but at the same time expanded other lines elsewhere in the US. This means that job losses in some regions subsidized new jobs in other parts of the country.</p>\n\n\n\n<p>On the whole, Magyari finds that although Chinese imports may have reduced employment within some establishments, these losses were more than offset by gains in employment within the same firms in other places. This is no consolation to people who lost their job. But it is necessary to add this perspective to the simplistic story of “trade with China is bad for US workers”.</p>\n\n\n\n<h4>Evidence from the expansion of trade in India and the impact on poverty reductions</h4>\n\n\n\n<p>Another important paper in this field is Topalova (2010): “Factor immobility and regional impacts of trade liberalization: Evidence on poverty from India”.{ref}Topalova, P. (2010). Factor immobility and regional impacts of trade liberalization: Evidence on poverty from India. American Economic Journal: Applied Economics, 2(4), 1-41. Available online <a rel=\"noreferrer noopener\" href=\"http://dl.kli.re.kr/dl_image/IMG/03/000000012162/SERVICE/000000012162_01.PDF\" target=\"_blank\">here</a>.{/ref}</p>\n\n\n\n<p>In this paper Topalova looks at the impact of trade liberalization on poverty across different regions in India, using the sudden and extensive <a href=\"https://ourworldindata.org/grapher/trade-as-share-of-gdp?country=IND\">change</a> in India’s trade policy in 1991. She finds that rural regions that were more exposed to liberalization, experienced a slower decline in poverty, and had lower consumption growth.</p>\n\n\n\n<p>In the analysis of the mechanisms underlying this effect, Topalova finds that liberalization had a stronger negative impact among the least geographically mobile at the bottom of the income distribution, and in places where labor laws deterred workers from reallocating across sectors.</p>\n\n\n\n<p>The evidence from India shows that (i) discussions that only look at “winners” in poor countries and “losers” in rich countries miss the point that the gains from trade are unequally distributed within both sets of countries; and (ii) context-specific factors, like worker mobility across sectors and geographic regions, are crucial to understand the impact of trade on incomes.</p>\n\n\n\n<h4>Evidence from other studies</h4>\n\n\n\n<ul><li>Donaldson (2018) uses archival data from colonial India to estimate the impact of India\u2019s vast railroad network. He finds railroads increased trade, and in doing so they increased real incomes (and reduced income volatility).{ref}Donaldson, D. (2018). Railroads of the Raj: Estimating the impact of transportation infrastructure. American Economic Review, 108(4-5), 899-934. Available online <a rel=\"noreferrer noopener\" href=\"http://eprints.lse.ac.uk/38368/1/ARCWP41-Donaldson.pdf\" target=\"_blank\">here</a>.{/ref}</li><li> Porto (2006) looks at the distributional effects of <a rel=\"noreferrer noopener\" href=\"https://en.wikipedia.org/wiki/Mercosur\" target=\"_blank\">Mercosur</a> on Argentine families, and finds this regional trade agreement led to benefits across the entire income distribution. He finds the effect was progressive: poor households gained more than middle-income households, because prior to the reform, trade protection benefitted the rich disproportionately.{ref}Porto, G (2006). Using Survey Data to Assess the Distributional Effects of Trade Policy. Journal of International Economics 70 (2006) 140\u2013160.{/ref}</li><li>Trefler (2004) looks at the Canada-US Free Trade Agreement and finds there was a group who bore “adjustment costs” (displaced workers and struggling plants) and a group who enjoyed “long-run gains” (consumers and efficient plants). {ref}Trefler, D. (2004). The long and short of the Canada-US free trade agreement. American Economic Review, 94(4), 870-895. Available online <a rel=\"noreferrer noopener\" href=\"https://www.aeaweb.org/articles?id=10.1257/0002828042002633\" target=\"_blank\">here</a>.{/ref}</li></ul>\n" } }, "extensions": { "debug": [ { "type": "DEBUG_LOGS_INACTIVE", "message": "GraphQL Debug logging is not active. To see debug logs, GRAPHQL_DEBUG must be enabled." } ] } } |