Distance and Political Boundaries: Estimating Border Effects under Inequality Constraints

Fernando  Borraz; Alberto  Cavallo; Roberto  Rigobon; Leandro  Zipitria

Article | International Journal of Finance & Economics

Distance and Political Boundaries: Estimating Border Effects under Inequality Constraints

by Fernando Borraz, Alberto Cavallo, Roberto Rigobon and Leandro Zipitria

Abstract

The border effects literature finds that political boundaries have a large impact on relative prices across locations. In this paper we show that the standard empirical specification suffers from selection bias, and propose a new methodology based on binned-quantile regressions. We use a novel micro-price dataset from Uruguay and focus on city borders. We find that when the standard methodology is used, two supermarkets separated by 10 kilometers across two different cities have the same price dispersion as two supermarkets separated by 30 kilometers within the same city, implying that crossing a city border is equivalent to tripling the distance. By contrast, when upper quantiles are used the city border effect disappears. These findings imply that transport costs have been systematically underestimated by previous literature. Our methodology can be applied to measure any kind of border effect. We illustrate this in the context of online-offine price dispersion to measure an online border effect in the city of Montevideo.

Keywords: border effects; prices;

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Borraz, Fernando, Alberto Cavallo, Roberto Rigobon, and Leandro Zipitria. "Distance and Political Boundaries: Estimating Border Effects under Inequality Constraints." International Journal of Finance & Economics 21, no. 1 (January 2016): 3–35.

As 2018 drew to a close, India prepared to once again carry out the largest democratic exercise in human history, as in less than six months more than 850 million eligible voters would have the chance to choose their representatives to the Lok Sabha—the country’s lower house of parliament—and, thus, their country’s Prime Minister and cabinet. The election would pit the ruling party—the Bharatiya Janata Party (Indian People’s Party, known as the BJP) led by Prime Minister Narendra Modi—against a collection of parties that included the once-dominant Indian National Congress party (Congress). The 2019 elections would serve as a referendum on Modi’s first term in office and, therefore, on a high stakes question: had India’s implausibly robust democracy produced the right leader for the right moment, or had it taken the wrong path?

We use data collected at the border and at retailers to characterize the impact of recent changes in US trade policy on importers, consumers, and exporters. We start by studying the tariffs on imports of steel and Chinese goods that were imposed during 2018. We find little difference in the "at-the-dock" ex-tariff price levels and stickiness for otherwise equivalent goods that were affected and not affected. This nearly complete passthrough of tariffs to the total price paid by importers suggests the tariff incidence has fallen largely on the US. We simultaneously estimate exchange rate passthrough and find the response to be far more muted. Next, in-progress analyses of retail prices preliminarily show more heterogeneity, with the higher cost of imports passed through to consumers for some goods, such as washing machines, but absorbed by lower retailer profit margins for others, such as many from China. Finally, in contrast to imports, US exports subjected to retaliatory tariffs exhibited declines in their ex-tariff prices relative to equivalent but non-targeted goods.

Case | HBS Case Collection | February 2019 (Revised May 2019)

The U.S. – China Trade War

Alberto Cavallo, Mariana Cal and Anne Laski

On December 1, 2018, U.S. President Donald Trump and China’s Leader Xi Jinping faced each other across a dinner table during a G20 meeting in Buenos Aires, Argentina. After what Trump called an “amazing and productive meeting,” the two leaders announced a truce in the ongoing trade war between their countries, following months of accusations, tariffs, and mounting retaliation. The U.S. agreed to postpone for 90 days an increase from 10% to 25% in tariffs applied to a large number of Chinese goods, which had been initially scheduled for January 1, 2019. In exchange, the White House announced that China would purchase a “very substantial” amount of agricultural and other products from the United States, adding that it expected the two nations “to immediately begin negotiations on structural changes with respect to forced technology transfer, intellectual property protection, non-tariff barriers, cyber intrusions and cyber theft, services, and agriculture.” The Chinese government simply stated that it was “willing to expand imports according to the needs of the domestic market” and that it hoped to “reach a concrete agreement on mutual benefit and win-win as soon as possible." Despite Trump’s assurances that China was sending “very strong signals” after the meeting, the outcome of the negotiations was highly uncertain. Would China provide enough concessions to satisfy the demands of the U.S.? Would the U.S. back down? Or would the trade war escalate, causing unprecedented disruptions—and opportunities—in global trade patterns?

Keywords: Trade War; Trump; current account; NAFTA; balance of payments; Intellectual Property Protection; Trade; Macroeconomics; Economic Slowdown and Stagnation; International Relations; United States; China;

Citation:

Cavallo, Alberto, Mariana Cal, and Anne Laski. "The U.S. – China Trade War." Harvard Business School Case 719-034, February 2019. (Revised May 2019.) View Details

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Distance and Political Boundaries: Estimating Border Effects under Inequality Constraints

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