Papers Containing Tag(s): 'Employer Identification Numbers'
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Viewing papers 71 through 80 of 191
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Working PaperDoes Goliath Help David? Anchor Firms and Startup Clusters
May 2020
Working Paper Number:
CES-20-17
This paper investigates the effects of a large firm's geographical expansion (anchor firm) on local worker transitions into young firms through wage effects in industries economically proximate to the anchor firm. Using hand-collected data matched to administrative Census microdata, I exploit anchor firms' site selection processes to employ a difference-in-differences approach to compare workers in winning counties to those in counterfactual counties. The arrival of an anchor firm induces worker reallocation towards young firms in industries linked through input-output channels by a magnitude of 120 new businesses that account for approximately 2,300 jobs. Consistent with the literature in personnel and organizational economics, incumbent firms experiencing the fastest wage growth due to these shocks shed mid-layer employees who select into young firms within the county and in their own industry of experience. These effects are strongest in the most specialized and knowledge-intensive industries. Attracting an anchor firm to a county appears to have limited spillover effects in overall employment that are mainly driven by reorganization of incumbent firms in the anchor's input-output industries that face rising labor costs.View Full Paper PDF
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Working PaperMeasuring the Effect of COVID-19 on U.S. Small Businesses: The Small Business Pulse Survey
May 2020
Working Paper Number:
CES-20-16
In response to the novel coronavirus (COVID-19) pandemic, the Census Bureau developed and fielded an entirely new survey intended to measure the effect on small businesses. The Small Business Pulse Survey (SBPS) will run weekly from April 26 to June 27, 2020. Results from the SBPS will be published weekly through a visualization tool with downloadable data. We describe the motivation for SBPS, summarize how the content for the survey was developed, and discuss some of the initial results from the survey. We also describe future plans for the SBPS collections and for our research using the SBPS data. Estimates from the first week of the SBPS indicate large to moderate negative effects of COVID-19 on small businesses, and yet the majority expect to return to usual level of operations within the next six months. Reflecting the Census Bureau's commitment to scientific inquiry and transparency, the micro data from the SBPS will be available to qualified researchers on approved projects in the Federal Statistical Research Data Center network.View Full Paper PDF
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Working PaperR&D or R vs. D? Firm Innovation Strategy and Equity Ownership
April 2020
Working Paper Number:
CES-20-14
We analyze a unique dataset that separately reports research and development expenditures for a large panel of public and private firms. Definitions of 'research' and 'development' in this dataset, respectively, correspond to definitions of knowledge 'exploration' and 'exploitation' in the innovation theory literature. We can thus test theories of how equity ownership status relates to innovation strategy. We find that public firms have greater research intensity than private firms, inconsistent with theories asserting private ownership is more conducive to exploration. We also find public firms invest more intensely in innovation of all sorts. These results suggest relaxed financing constraints enjoyed by public firms, as well as their diversified shareholder bases, make them more conducive to investing in all types of innovation. Reconciling several seemingly conflicting results in prior research, we find private-equity-owned firms, though not less innovative overall than other private firms, skew their innovation strategies toward development and away from research.View Full Paper PDF
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Working PaperAre Customs Records Consistent Across Countries? Evidence from the U.S. and Colombia
March 2020
Working Paper Number:
CES-20-11
In many countries, official customs records include identifying information on the exporting and importing firms involved in each shipment. This information allows researchers to study international business networks, offshoring patterns, and the micro-foundations of aggregate trade flows. It also provides the government with a basis for tariff assessments at the border. However, there are no mechanisms in place to ensure that the shipment-level information recorded by the exporting country is consistent with the shipment-level information recorded by the importing country. And to the extent that there are discrepancies, it is not clear how prevalent they are or what form they take. In this paper we explore these issues, both to enhance our understanding of the limitations of customs records, and to inform future discussions of possible revisions in the way they are collected. Specifically, we match U.S.-bound export shipments that appear in Colombian Customs records (DIAN) with their counterparts in the US Customs records (LFTTD): U.S. import shipments from Colombia. Several patterns emerge. First, differences in the coverage of the two countries customs records lead to significant discrepancies in the official bilateral trade flow statistics of these two countries: the DIAN database records 8 percent fewer transactions than the LFTTD database over the sample period, and the average export shipment size in the DIAN is roughly 4 percent smaller than the corresponding import shipment size in the LFTTD. These discrepancies are not due to difference in minimum shipment sizes and they are not particular to a few sectors, though they are more common among small shipments and they evolve over time. Second, if we rely exclusively on firms' names and addresses, ignoring other shipment characteristics (value, product code, etc.), we are able to match 85 percent of the value of U.S. imports from Colombia in our LFTTD sample with particular Colombian suppliers in the DIAN. Further, fully 97 percent of the value of Colombian exports to the U.S. can be mapped onto particular importers in the U.S. LFTTD. Third, however, match rates at the shipment level within buyer-seller pairs are low. That is, while buyers and sellers can be paired up fairly accurately, only 25-30 percent of the individual transactions in the customs records of the two countries can be matched using fuzzy algorithms at reasonable tolerance levels. Fourth, the manufacturer ID (MANUF_ID) that appears in the LFTTD implies there are roughly twice as many Colombian exporters as actually appear in the DIAN. And similar comments apply to an analogous MANUF_ID variable constructed from importer name and address information in the DIAN. Hence studies that treat each MANUF_ID value as a distinct firm are almost surely overstating the number of foreign firms that engage in trade with the U.S. by a substantial amount. Finally, we conclude that if countries were to require that exporters report standardized shipment identifiers'either invoice numbers or bill of lading/air waybill numbers'it would be far easier to track individual transactions and to identify international discrepancies in reporting.View Full Paper PDF
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Working PaperBetween Firm Changes in Earnings Inequality: The Dominant Role of Industry Effects
February 2020
Working Paper Number:
CES-20-08
We find that most of the rising between firm earnings inequality that dominates the overall increase in inequality in the U.S. is accounted for by industry effects. These industry effects stem from rising inter-industry earnings differentials and not from changing distribution of employment across industries. We also find the rising inter-industry earnings differentials are almost completely accounted for by occupation effects. These results link together the key findings from separate components of the recent literature: one focuses on firm effects and the other on occupation effects. The link via industry effects challenges conventional wisdom.View Full Paper PDF
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Working PaperDo Cash Windfalls Affect Wages? Evidence from R&D Grants to Small Firms
February 2020
Working Paper Number:
CES-20-06
This paper examines how employee earnings at small firms respond to a cash flow shock in the form of a government R&D grant. We use ranking data on applicant firms, which we link to IRS W2 earnings and other U.S. Census Bureau datasets. In a regression discontinuity design, we find that the grant increases average earnings with a rent-sharing elasticity of 0.07 (0.21) at the employee (firm) level. The beneficiaries are incumbent employees who were present at the firm before the award. Among incumbent employees, the effect increases with worker tenure. The grant also leads to higher employment and revenue, but productivity growth cannot fully explain the immediate effect on earnings. Instead, the data and a grantee survey are consistent with a backloaded wage contract channel, in which employees of financially constrained firms initially accept relatively low wages and are paid more when cash is available.View Full Paper PDF
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Working PaperMatching State Business Registration Records to Census Business Data
January 2020
Working Paper Number:
CES-20-03
We describe our methodology and results from matching state Business Registration Records (BRR) to Census business data. We use data from Massachusetts and California to develop methods and preliminary results that could be used to guide matching data for additional states. We obtain matches to Census business records for 45% of the Massachusetts BRR records and 40% of the California BRR records. We find higher match rates for incorporated businesses and businesses with higher startup-quality scores as assigned in Guzman and Stern (2018). Clerical reviews show that using relatively strict matching on address is important for match accuracy, while results are less sensitive to name matching strictness. Among matched BRR records, the modal timing of the first match to the BR is in the year in which the BRR record was filed. We use two sets of software to identify matches: SAS DQ Match and a machine-learning algorithm described in Cuffe and Goldschlag (2018). We find preliminary evidence that while the ML-based method yields more match results, SAS DQ tends to result in higher accuracy rates. To conclude, we provide suggestions on how to proceed with matching other states' data in light of our findings using these two states.View Full Paper PDF
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Working PaperNonemployer Statistics by Demographics (NES-D): Exploring Longitudinal Consistency and Sub-national Estimates
December 2019
Working Paper Number:
CES-19-34
Until recently, the quinquennial Survey of Business Owners (SBO) was the only source of information for U.S. employer and nonemployer businesses by owner demographic characteristics such as race, ethnicity, sex and veteran status. Now, however, the Nonemployer Statistics by Demographics series (NES-D) will replace the SBO's nonemployer component with reliable, and more frequent (annual) business demographic estimates with no additional respondent burden, and at lower imputation rates and costs. NES-D is not a survey; rather, it exploits existing administrative and census records to assign demographic characteristics to the universe of approximately 25 million (as of 2016) nonemployer businesses. Although only in the second year of its research phase, NES-D is rapidly moving towards production, with a planned prototype or experimental version release of 2017 nonemployer data in 2020, followed by annual releases of the series. After the first year of research, we released a working paper (Luque et al., 2019) that assessed the viability of estimating nonemployer demographics exclusively with administrative records (AR) and census data. That paper used one year of data (2015) to produce preliminary tabulations of business counts at the national level. This year we expand that research in multiple ways by: i) examining the longitudinal consistency of administrative and census records coverage, and of our AR-based demographics estimates, ii) evaluating further coverage from additional data sources, iii) exploring estimates at the sub-national level, iv) exploring estimates by industrial sector, v) examining demographics estimates of business receipts as well as of counts, and vi) implementing imputation of missing demographic values. Our current results are consistent with the main findings in Luque et al. (2019), and show that high coverage and demographic assignment rates are not the exception, but the norm. Specifically, we find that AR coverage rates are high and stable over time for each of the three years we examine, 2014-2016. We are able to identify owners for approximately 99 percent of nonemployer businesses (excluding C-corporations), 92 to 93 percent of identified nonemployer owners have no missing demographics, and only about 1 percent are missing three or more demographic characteristics in each of the three years. We also find that our demographics estimates are stable over time, with expected small annual changes that are consistent with underlying population trends in the U.S.. Due to data limitations, these results do not include C-corporations, which represent only 2 percent of nonemployer businesses and 4 percent of receipts. Without added respondent burden and at lower imputation rates and costs, NES-D will provide high-quality business demographics estimates at a higher frequency (annual vs. every 5 years) than the SBO.View Full Paper PDF
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Working PaperFounding Teams and Startup Performance
November 2019
Working Paper Number:
CES-19-32
We explore the role of founding teams in accounting for the post-entry dynamics of startups. While the entrepreneurship literature has largely focused on business founders, we broaden this view by considering founding teams, which include both the founders and the initial employees in the first year of operations. We investigate the idea that the success of a startup may derive from the organizational capital that is created at firm formation and is inalienable from the founding team itself. To test this hypothesis, we exploit premature deaths to identify the causal impact of losing a founding team member on startup performance. We find that the exogenous separation of a founding team member due to premature death has a persistently large, negative, and statistically significant impact on post-entry size, survival, and productivity of startups. While we find that the loss of a key founding team member (e.g. founders) has an especially large adverse effect, the loss of a non-key founding team member still has a significant adverse effect, lending support to our inclusive definition of founding teams. Furthermore, we find that the effects are particularly strong for small founding teams but are not driven by activity in small business-intensive or High Tech industries.View Full Paper PDF
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Working PaperForeign vs. U.S. Graduate Degrees: The Impact on Earnings Assimilation and Return Migration for the Foreign Born
June 2019
Working Paper Number:
CES-19-17
Using a novel panel data set of recent immigrants to the U.S., we identify return migration rates and earnings trajectories of two immigrant groups: those with foreign graduate degrees and those with a U.S. graduate degree. We focus on immigrants (of both genders) to the U.S. who arrive in the same entry cohort and from the same country of birth over the period 2005-2015. In Census-IRS administrative data, we find that downward earnings trajectories are predictive of return migration for immigrants with degrees acquired abroad. Meanwhile, immigrants with U.S.-acquired graduate degrees experience mainly upward earnings mobility.View Full Paper PDF
