Center for Global Management

YOU ARE NOT WELCOME: CAUSES AND EFFECTS OF NATIONALISTIC SENTIMENT TOWARDS FOREIGN FIRMS (2020-21)

Pedro Makhoul

Ph.D. student in strategy (entered 2017) (continuation of 2019-20 award)

Over the past few years, there has been a significant rise in populism and nationalistic narratives around the globe. For companies looking to expand or increase operations overseas, this is one more obstacle to overcome. Nationalistic rhetoric fosters the idea of “us versus them” and thus makes it harder for both trade relationships (imports and exports) and foreign firms operating overseas (multinationals) to function properly. Management scholars have long discussed the idea that foreign firms trying to do business abroad experience some disadvantages vis-à-vis domestic firms. This concept is known as “liability of foreignness” (LOF), and its sources can be broadly categorized into two types; namely, the costs associated with an unfamiliar environment hazard and the costs related to a discrimination hazard.

Pedro Makhoul’s research seeks to contribute to the discrimination hazard and mergers and acquisitions (M&A) literature in three main ways: first, by directly measuring the nationalistic sentiment across four U.S. states using experimental methodology to quantify the anti-foreign sentiment in each of these locations; second, by understanding how public opinion influences real business outcomes when it comes to the context of foreign acquisitions; and third, through an enhanced understanding of the origins of nationalistic sentiments and where anti-foreign sentiment stems from.

The CGM’s support, a continuation of the 2019-20 award, has provided a significant contribution to the progress of Makhoul’s research. Last year, the experimental component was approved by UCLA’s Institutional Review Board (which reviews the conduct of research using human subjects), and much of the data collection on the four states (California, Massachusetts, Minnesota and New York) as well as immigration and M&A data gathering was completed. Funding over the two years has been paramount in kick-starting the experimental part of the research. Funding has been used to distribute surveys and collect large sample data through online survey platforms, such as Amazon’s Mechanical Turk and Lucid, and enabled Makhoul to explore regional variation within the U.S. and draw inferences.

Preliminary regressions show a statistically significant difference between the implicit valuation of acquisitions made by foreign versus domestic firms (foreign firms appear to pay a larger premium to acquire U.S. firms). Preliminary findings from online experiments also suggest there is heterogeneity both within and across states on the likelihood of an individual choosing to veto a foreign acquisition of a U.S. firm. Furthermore, the data suggests that immigration patterns from the mid-19th century play a role in shaping people’s perceptions to this day.

Findings from this project are of great business and management relevance. Makhoul’s research addresses fundamental questions for companies seeking to expand operations abroad; namely, what are the costs and disadvantages of doing business abroad and entering foreign markets, and how will these barriers affect operations and profits? This research is part of Makhoul’s doctoral dissertation and will form the basis of his job market paper at the end of the year. He will also be submitting the paper to various top economic and strategy journals and publications.

A SIMPLE, CONSISTENT AND ACCURATE MEASUREMENT AND MODEL OF CHINA’S G.D.P.
(2020-21)

William Yu

lecturer of global economics and management and economist, UCLA Anderson Forecast

While William Yu has an extensive understanding of the world’s second largest economy, he also recognizes the need for a more accurate measurement of China’s gross domestic product (GDP). Currently, estimates rely only on data from the Chinese government. While the World Bank, International Monetary Fund and United Nations need to rely on China’s official statistics, some organizations have switched to looking at alternative indicators, such as China’s purchasing managers indices (PMIs). The goal of Yu’s research is to develop a simple, consistent and more accurate measurement of the aggregate economic activities of China, on a quarterly basis, that incorporates additional variables and datasets and provides a supporting theoretic framework to more accurately forecast China’s GDP in the future.

Yu’s research includes an examination of data from the National Bureau of Statistics of China and a study of China’s international trade data to enable an analysis of imports and exports over time and a comparison of the correlation between international trade and GDP growth. His model will incorporate data from various PMIs, including the Caixin China General Services PMI. Financial statements of public Chinese companies will be reviewed to shed light on production and consumption. Pollution and satellite image data will also be considered. Yu’s model will also factor in the importance of these variables and place a weight on them to calculate the coefficient of their contributions to China’s GDP growth.

Funding from the CGM was used to hire Cara Rose Keogh, a rising senior and double major in business economics and Chinese, who is providing research assistance and support. Keogh is conducting a literature review of the Chinese economy and its measurement of GDP; searching relevant reports and datasets; and collecting, organizing and managing the data. Yu also plans to use funding to purchase proprietary datasets that will further assist with measuring and assessing China's economic activities.

Findings from this research will be of great interest to global leaders and businesses around the world. The estimated GDP growth generated by this model will be published by the Anderson Forecast and used by its economists. Yu is also preparing a working paper that will form the basis of submissions to top economic journals and publications.

WHAT DETERMINES THE INDUSTRY SPECIALIZATION OF LOCATIONS: EUROPEAN IMMIGRANTS AND THE LOCATION OF U.S. INDUSTRIES (2019-20)

Sebastian Ottinger

Ph.D. student in global economics and management (entered 2016)

Silicon Valley employs more people in the IT industry than any other location in the U.S. Detroit employs more people in the auto industry than any other comparably sized city. Such clustering of industries in a few locations is common in the manufacturing sector. How do we explain where industries cluster?

Ottinger’s research helps to answer this question. When explaining the reason why specific locations are centers of industries, he purports that it is essential to understand how they became such centers in the first place. Anecdotal evidence suggests that where initial pioneers locate is a contributing factor. Early starts give locations a “first-mover” advantage and help them become and remain national and regional industrial centers.

Yet providing systematic empirical evidence that supports this account has proven difficult. Entrepreneurs choose where they set up shop wisely. Ottinger advocates that many European immigrants arriving in the second half of the 19th century were among such pioneers for the manufacturing belt in the United States. His research predicts that where immigrants set up shop was based on the settlement patterns of earlier immigrants. These earlier immigrants — predominantly farmers — chose locations because they were suitable for agriculture, not manufacturing. However, the immigrants that arrived later brought skills and knowledge to the then-novel manufacturing sector and set up pioneer establishments where the earlier immigrants had settled. Ottinger identifies the sectors that these immigrants were experienced and skilled in using historical trade data and calculating European origin countries’ specialization across various industries in the manufacturing sector. His research suggests that immigrants promoted the establishment of regional and national centers for manufacturing-based industries in the U.S. and that these locations have tended to remain centers until the present day.

The CGM support made a significant contribution to the progress of Ottinger’s research. Funding was used to hire a data digitization specialist to gather data on all traded goods and imports into the U.S. by trading partners in 1851, 1881 and 1909. This allowed Ottinger to manually match traded goods to particular manufacturing industries and then use this as a historical measure of specialization in manufacturing, thus strengthening the paper’s findings immensely. It also provided Ottinger the first harmonized data set on specialization at highly disaggregated industry levels covering almost all industrialized nations during the “First Globalization” from 1870 to 1914. Ottinger will make this data publicly available and is certain that this data source will find further uses to answer interesting questions in other domains by researchers around the world. Ottinger has disseminated his results widely and presented the findings in seminars at Harvard, Boston, and Brown universities. He also has presented the paper at two sessions of the National Bureau of Economic Research’s Summer Institute, as well as at the Econometric Society World Congress and Congress of the European Economic Association. The paper will be Ottinger’s job market paper at the end of the year. He is now working on two spin-off projects strongly related to the research.