Andreas Beerli, J. Ruffner, Michael Siegenthaler, G. Peri
We study a reform that granted European cross-border workers free access to the Swiss labor market and had a stronger effect on regions close to the border. The greater availability of cross-border workers increased foreign employment substantially. Although many cross-border workers were highly educated, wages of highly educated natives increased. The reason is a simultaneous increase in labor demand: the reform increased the size, productivity, and innovation performance of skill-intensive incumbent firms and attracted new firms, creating opportunities for natives to pursue managerial jobs. These effects are mainly driven by firms that reported skill shortages before the reform. (JEL J15, J23, J24, J31, J61, K37)
{"title":"The Abolition of Immigration Restrictions and the Performance of Firms and Workers: Evidence from Switzerland","authors":"Andreas Beerli, J. Ruffner, Michael Siegenthaler, G. Peri","doi":"10.3386/W25302","DOIUrl":"https://doi.org/10.3386/W25302","url":null,"abstract":"We study a reform that granted European cross-border workers free access to the Swiss labor market and had a stronger effect on regions close to the border. The greater availability of cross-border workers increased foreign employment substantially. Although many cross-border workers were highly educated, wages of highly educated natives increased. The reason is a simultaneous increase in labor demand: the reform increased the size, productivity, and innovation performance of skill-intensive incumbent firms and attracted new firms, creating opportunities for natives to pursue managerial jobs. These effects are mainly driven by firms that reported skill shortages before the reform. (JEL J15, J23, J24, J31, J61, K37)","PeriodicalId":276603,"journal":{"name":"Kauffman: Conferences & Seminars (Topic)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127549446","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Cloud computing—computing done on an off-site network of resources accessed through the Internet—is revolutionizing how computing services are used. However, because cloud is so new and it largely is an intermediate input to other industries, it is difficult to track in the U.S. statistical system. Moreover, there is a paucity of systematic information on the prices of cloud services. To begin filling this gap, this paper does three things. First, we define the different segments of cloud computing and document its explosive expansion. Second, we develop new hedonic prices indexes for cloud services based on quarterly data for compute, database, and storage services offered by Amazon Web Services (AWS) from 2009 to 2016. These indexes fall rapidly over the sample period, with quickening (and double digit) rates of decline for all three products starting at the beginning of 2014. Finally, we highlight the puzzle of why investment in IT equipment in the NIPAs has been so weak while capital expenditures have exploded for IT equipment associated with cloud infrastructure. We suggest that cloud service providers are undertaking large amounts of own-account investment in IT equipment and that some of this investment may not be captured in GDP.
{"title":"The Rise of Cloud Computing: Minding Your P’S, Q's and K's","authors":"David M. Byrne, C. Corrado, Daniel E. Sichel","doi":"10.3386/W25188","DOIUrl":"https://doi.org/10.3386/W25188","url":null,"abstract":"Cloud computing—computing done on an off-site network of resources accessed through the Internet—is revolutionizing how computing services are used. However, because cloud is so new and it largely is an intermediate input to other industries, it is difficult to track in the U.S. statistical system. Moreover, there is a paucity of systematic information on the prices of cloud services. To begin filling this gap, this paper does three things. First, we define the different segments of cloud computing and document its explosive expansion. Second, we develop new hedonic prices indexes for cloud services based on quarterly data for compute, database, and storage services offered by Amazon Web Services (AWS) from 2009 to 2016. These indexes fall rapidly over the sample period, with quickening (and double digit) rates of decline for all three products starting at the beginning of 2014. Finally, we highlight the puzzle of why investment in IT equipment in the NIPAs has been so weak while capital expenditures have exploded for IT equipment associated with cloud infrastructure. We suggest that cloud service providers are undertaking large amounts of own-account investment in IT equipment and that some of this investment may not be captured in GDP.","PeriodicalId":276603,"journal":{"name":"Kauffman: Conferences & Seminars (Topic)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127614821","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yujin Kim, Chirantan Chatterjee, Matthew J. Higgins
Can regulation reduce risks associated with investing in early-stage firms? Using the passage of the European Orphan Drug Act (EU-ODA), we examine this question in the biopharmaceutical industry. We provide causal evidence that venture capitalists (VCs) are more likely to invest in early-stage firms operating in sub-fields disproportionately affected by EU-ODA. The switch to early-stage investments appears strongest among VCs that previously faced greater levels of information asymmetry. We also find that the level of syndication declined for early-stage investments and exit performance improved. We conclude discussing the implications of our findings for public policy, entrepreneurship and innovation.
{"title":"Moving Beyond the Valley of Death: Regulation and Venture Capital Investments in Early-Stage Biopharmaceutical Firms","authors":"Yujin Kim, Chirantan Chatterjee, Matthew J. Higgins","doi":"10.2139/ssrn.3309496","DOIUrl":"https://doi.org/10.2139/ssrn.3309496","url":null,"abstract":"Can regulation reduce risks associated with investing in early-stage firms? Using the passage of the European Orphan Drug Act (EU-ODA), we examine this question in the biopharmaceutical industry. We provide causal evidence that venture capitalists (VCs) are more likely to invest in early-stage firms operating in sub-fields disproportionately affected by EU-ODA. The switch to early-stage investments appears strongest among VCs that previously faced greater levels of information asymmetry. We also find that the level of syndication declined for early-stage investments and exit performance improved. We conclude discussing the implications of our findings for public policy, entrepreneurship and innovation.","PeriodicalId":276603,"journal":{"name":"Kauffman: Conferences & Seminars (Topic)","volume":"113 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132392673","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Income disparity across countries has been large and widening over time. We develop a tractable model where factor requirements in production technology do not necessarily match a country's factor input profile. Appropriate assimilation of frontier technologies balances such multi-dimensional factor input-technology mismatch, thus mitigating the efficiency loss. This yields a new measure for endogenous TFP, entailing a novel trade-off between a country's income level and income growth that depends critically on the assimilation ability and the factor input mismatch. Our baseline model accounts for 80%-92% of the global income variation over the past 50 years. The widening of mismatch and heterogeneity in the assimilation ability account for 41% and 20% of the global growth variation, whereas physical capital accounts for about one third with human capital largely inconsequential. In particular, about 30% of the output growth in miracle Asian economies comes from narrowing the gap arisen from mismatch, and 94% of the growth stagnation in trapped African economies due to the widening mismatch. A country may fall into a middle-income trap after a factor advantage reversal that changes the pattern of mismatch.
{"title":"Mismatch and Assimilation","authors":"Ping Wang, Tsz-Nga Wong, C. Yip","doi":"10.3386/W24960","DOIUrl":"https://doi.org/10.3386/W24960","url":null,"abstract":"Income disparity across countries has been large and widening over time. We develop a tractable model where factor requirements in production technology do not necessarily match a country's factor input profile. Appropriate assimilation of frontier technologies balances such multi-dimensional factor input-technology mismatch, thus mitigating the efficiency loss. This yields a new measure for endogenous TFP, entailing a novel trade-off between a country's income level and income growth that depends critically on the assimilation ability and the factor input mismatch. Our baseline model accounts for 80%-92% of the global income variation over the past 50 years. The widening of mismatch and heterogeneity in the assimilation ability account for 41% and 20% of the global growth variation, whereas physical capital accounts for about one third with human capital largely inconsequential. In particular, about 30% of the output growth in miracle Asian economies comes from narrowing the gap arisen from mismatch, and 94% of the growth stagnation in trapped African economies due to the widening mismatch. A country may fall into a middle-income trap after a factor advantage reversal that changes the pattern of mismatch.","PeriodicalId":276603,"journal":{"name":"Kauffman: Conferences & Seminars (Topic)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124908665","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We demonstrate that data from digital platforms such as Yelp have the potential to improve our understanding of gentrification, both by providing data in close to real time (i.e. nowcasting and forecasting) and by providing additional context about how the local economy is changing. Combining Yelp and Census data, we find that gentrification, as measured by changes in the educational, age, and racial composition within a ZIP code, is strongly associated with increases in the numbers of grocery stores, cafes, restaurants, and bars, with little evidence of crowd-out of other categories of businesses. We also find that changes in the local business landscape is a leading indicator of housing price changes, and that the entry of Starbucks (and coffee shops more generally) into a neighborhood predicts gentrification. Each additional Starbucks that enters a zip code is associated with a 0.5% increase in housing prices.
{"title":"Measuring Gentrification: Using Yelp Data to Quantify Neighborhood Change","authors":"E. Glaeser, Hyunjin Kim, Michael Luca","doi":"10.3386/w24952","DOIUrl":"https://doi.org/10.3386/w24952","url":null,"abstract":"We demonstrate that data from digital platforms such as Yelp have the potential to improve our understanding of gentrification, both by providing data in close to real time (i.e. nowcasting and forecasting) and by providing additional context about how the local economy is changing. Combining Yelp and Census data, we find that gentrification, as measured by changes in the educational, age, and racial composition within a ZIP code, is strongly associated with increases in the numbers of grocery stores, cafes, restaurants, and bars, with little evidence of crowd-out of other categories of businesses. We also find that changes in the local business landscape is a leading indicator of housing price changes, and that the entry of Starbucks (and coffee shops more generally) into a neighborhood predicts gentrification. Each additional Starbucks that enters a zip code is associated with a 0.5% increase in housing prices.","PeriodicalId":276603,"journal":{"name":"Kauffman: Conferences & Seminars (Topic)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117077591","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract What is the role of structural estimation in behavioral economics? I discuss advantages, and limitations, of the work in Structural Behavioral Economics. I also cover common modeling choices and how to get started. Among the advantages, I argue that structural estimation builds on, and expands, a classical behavioral tool, simple calibrations, and that it benefits from the presence of a few parsimonious behavioral models which can be taken to the data. Estimation is also well suited for experimental work, common in behavioral economics, as it can lead to improvements in the experimental design. In addition, at a time where policy implications of behavioral work are increasingly discussed, it is important to ground these policy implications in (estimated) models. Structural work, however, has important limitations, which are relevant to its behavioral applications. Estimation takes much longer and the extra degree of complexity can make it difficult to know which of a series of assumptions is driving the results. For related reasons, it is also easy to over-reach with the welfare implications. Taking this into account, I provide a partial how-to guide to structural behavioral economics, covering: (i) the choice of estimation method; (ii) the modeling of heterogeneity; (iii) identification and sensitivity. Finally, I discuss common issues for the estimation of leading behavioral models. I illustrate this discussion with selected coverage of existing work in the literature.
{"title":"Structural Behavioral Economics","authors":"Stefano DellaVigna","doi":"10.3386/W24797","DOIUrl":"https://doi.org/10.3386/W24797","url":null,"abstract":"Abstract What is the role of structural estimation in behavioral economics? I discuss advantages, and limitations, of the work in Structural Behavioral Economics. I also cover common modeling choices and how to get started. Among the advantages, I argue that structural estimation builds on, and expands, a classical behavioral tool, simple calibrations, and that it benefits from the presence of a few parsimonious behavioral models which can be taken to the data. Estimation is also well suited for experimental work, common in behavioral economics, as it can lead to improvements in the experimental design. In addition, at a time where policy implications of behavioral work are increasingly discussed, it is important to ground these policy implications in (estimated) models. Structural work, however, has important limitations, which are relevant to its behavioral applications. Estimation takes much longer and the extra degree of complexity can make it difficult to know which of a series of assumptions is driving the results. For related reasons, it is also easy to over-reach with the welfare implications. Taking this into account, I provide a partial how-to guide to structural behavioral economics, covering: (i) the choice of estimation method; (ii) the modeling of heterogeneity; (iii) identification and sensitivity. Finally, I discuss common issues for the estimation of leading behavioral models. I illustrate this discussion with selected coverage of existing work in the literature.","PeriodicalId":276603,"journal":{"name":"Kauffman: Conferences & Seminars (Topic)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116079179","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
B. Bosworth, John Bieler, M. Kleinrock, E. Koepcke, E. Berndt
The prescription drug component of the Consumer Price Index (CPI measures recent and past drug price changes, and provides the basis for projecting future price trends and health care expenditures. However, there are concerns about the adequacy of the price data because of recent changes in the structure of the market for prescription drugs. We compare the prescription drug data of the CPI with a large alternative data set from the IQVIA Institute for Human Data Science. We analyze the overall consistency if the data from the two sources, and examine the influence of the large shift from brand to generic drug sales and the increased reliance on third party insurance plans that are excluded from the CPI sampling frame.
{"title":"An Evaluation of the CPI Indexes for Prescription Drugs","authors":"B. Bosworth, John Bieler, M. Kleinrock, E. Koepcke, E. Berndt","doi":"10.3386/W24210","DOIUrl":"https://doi.org/10.3386/W24210","url":null,"abstract":"The prescription drug component of the Consumer Price Index (CPI measures recent and past drug price changes, and provides the basis for projecting future price trends and health care expenditures. However, there are concerns about the adequacy of the price data because of recent changes in the structure of the market for prescription drugs. We compare the prescription drug data of the CPI with a large alternative data set from the IQVIA Institute for Human Data Science. We analyze the overall consistency if the data from the two sources, and examine the influence of the large shift from brand to generic drug sales and the increased reliance on third party insurance plans that are excluded from the CPI sampling frame.","PeriodicalId":276603,"journal":{"name":"Kauffman: Conferences & Seminars (Topic)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128078269","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This Paper challenges two widely held views: first that trade performance has been the primary reason for the declining share of manufacturing employment in the United States and other industrial economies, and second that recent productivity growth in manufacturing has actually been quite rapid but is not accurately measured. The paper shows that for many decades, relatively faster productivity growth interacting with unresponsive demand has been the dominant force behind the declining share of employment in manufacturing in the United States and other industrial economies. It also shows that since 2010, however, the relationship has been reversed and slower productivity growth in manufacturing has been associated with more robust performance in manufacturing employment. These contrasting experiences suggest a tradeoff between the ability of the manufacturing sector to contribute to productivity growth and its ability to provide employment opportunities. While some blame measurement errors for the recently recorded slowdown in manufacturing productivity growth, spending patterns in the United States and elsewhere suggest that the productivity slowdown is real and that thus far fears about robots and other technological advances in manufacturing displacing large numbers of jobs appear misplaced.
{"title":"Recent Manufacturing Employment Growth: The Exception that Proves the Rule","authors":"Robert Z. Lawrence","doi":"10.3386/W24151","DOIUrl":"https://doi.org/10.3386/W24151","url":null,"abstract":"This Paper challenges two widely held views: first that trade performance has been the primary reason for the declining share of manufacturing employment in the United States and other industrial economies, and second that recent productivity growth in manufacturing has actually been quite rapid but is not accurately measured. The paper shows that for many decades, relatively faster productivity growth interacting with unresponsive demand has been the dominant force behind the declining share of employment in manufacturing in the United States and other industrial economies. It also shows that since 2010, however, the relationship has been reversed and slower productivity growth in manufacturing has been associated with more robust performance in manufacturing employment. These contrasting experiences suggest a tradeoff between the ability of the manufacturing sector to contribute to productivity growth and its ability to provide employment opportunities. While some blame measurement errors for the recently recorded slowdown in manufacturing productivity growth, spending patterns in the United States and elsewhere suggest that the productivity slowdown is real and that thus far fears about robots and other technological advances in manufacturing displacing large numbers of jobs appear misplaced.","PeriodicalId":276603,"journal":{"name":"Kauffman: Conferences & Seminars (Topic)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134039447","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Inequality is one of the main challenges posed by the proliferation of artificial intelligence (AI) and other forms of worker-replacing technological progress. This paper provides a taxonomy of the associated economic issues: First, we discuss the general conditions under which new technologies such as AI may lead to a Pareto improvement. Secondly, we delineate the two main channels through which inequality is affected – the surplus arising to innovators and redistributions arising from factor price changes. Third, we provide several simple economic models to describe how policy can counter these effects, even in the case of a “singularity” where machines come to dominate human labor. Under plausible conditions, non-distortionary taxation can be levied to compensate those who otherwise might lose. Fourth, we describe the two main channels through which technological progress may lead to technological unemployment – via efficiency wage effects and as a transitional phenomenon. Lastly, we speculate on how technologies to create super-human levels of intelligence may affect inequality and on how to save humanity from the Malthusian destiny that may ensue.
{"title":"Artificial Intelligence and its Implications for Income Distribution and Unemployment","authors":"Anton Korinek, J. Stiglitz","doi":"10.3386/W24174","DOIUrl":"https://doi.org/10.3386/W24174","url":null,"abstract":"Inequality is one of the main challenges posed by the proliferation of artificial intelligence (AI) and other forms of worker-replacing technological progress. This paper provides a taxonomy of the associated economic issues: First, we discuss the general conditions under which new technologies such as AI may lead to a Pareto improvement. Secondly, we delineate the two main channels through which inequality is affected – the surplus arising to innovators and redistributions arising from factor price changes. Third, we provide several simple economic models to describe how policy can counter these effects, even in the case of a “singularity” where machines come to dominate human labor. Under plausible conditions, non-distortionary taxation can be levied to compensate those who otherwise might lose. Fourth, we describe the two main channels through which technological progress may lead to technological unemployment – via efficiency wage effects and as a transitional phenomenon. Lastly, we speculate on how technologies to create super-human levels of intelligence may affect inequality and on how to save humanity from the Malthusian destiny that may ensue.","PeriodicalId":276603,"journal":{"name":"Kauffman: Conferences & Seminars (Topic)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130457283","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Chaoran Chen, Diego Restuccia, Raül Santaeulàlia-Llopis
We assess the effects of land markets on misallocation and productivity by exploiting policy-driven variation in land rentals across time and space arising from a large-scale land certification reform in Ethiopia, where land remains owned by the state. Our main finding from detailed micro panel data is that land rentals substantially reduce misallocation and increase agricultural productivity. Our evidence builds from an empirical difference-in-difference strategy, an instrumental variable approach, and a calibrated quantitative macroeconomic framework with heterogeneous household-farms that replicates, without targeting, the empirical effects. These effects are nonlinear, impacting more farms farther away from efficient operational scale, consistent with our theory. Using our model, we find that more active land markets reduce inequality, an important concern for the design of land policy. We also find that the positive effects of land markets are mainly driven by formal market rentals as opposed to informal rentals. Finally, our analysis also provides evidence that land markets increase the adoption of more advanced technologies such as the use of fertilizers.
{"title":"The Effects of Land Markets on Resource Allocation and Agricultural Productivity","authors":"Chaoran Chen, Diego Restuccia, Raül Santaeulàlia-Llopis","doi":"10.3386/w24034","DOIUrl":"https://doi.org/10.3386/w24034","url":null,"abstract":"We assess the effects of land markets on misallocation and productivity by exploiting policy-driven variation in land rentals across time and space arising from a large-scale land certification reform in Ethiopia, where land remains owned by the state. Our main finding from detailed micro panel data is that land rentals substantially reduce misallocation and increase agricultural productivity. Our evidence builds from an empirical difference-in-difference strategy, an instrumental variable approach, and a calibrated quantitative macroeconomic framework with heterogeneous household-farms that replicates, without targeting, the empirical effects. These effects are nonlinear, impacting more farms farther away from efficient operational scale, consistent with our theory. Using our model, we find that more active land markets reduce inequality, an important concern for the design of land policy. We also find that the positive effects of land markets are mainly driven by formal market rentals as opposed to informal rentals. Finally, our analysis also provides evidence that land markets increase the adoption of more advanced technologies such as the use of fertilizers.","PeriodicalId":276603,"journal":{"name":"Kauffman: Conferences & Seminars (Topic)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128535237","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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