scispace - formally typeset
Search or ask a question

Showing papers in "Research Papers in Economics in 2019"


Book ChapterDOI
TL;DR: In this paper, the authors identify, at a fundamental theoretical level, the impacts of privatization on the operations of an enterprise and present the delineation of various characteristics of an activity's structure and environment that point to either public or private forms of control as the most effective in accomplishing society's aims.
Abstract: This chapter identifies, at a fundamental theoretical level, the impacts of privatization on the operations of an enterprise. It aims to present the delineation of various characteristics of an activity's structure and environment that point to either public or private forms of control as the most effective in accomplishing society's aims. The chapter argues that at a fundamental level the intrinsic differences between public and private enterprise must ultimately be based on incentives, and these in turn are based on the available information. The labels "public ownership" and "private enterprise suggest two discrete and very different ways of structuring economic activity and utilizing productive assets. The corresponding simple view of privatization is that it inevitably and significantly alters the way in which resources are allocated. The conclusion that privatization typically has a major impact on the allocation of resources is probably correct.

342 citations


Book ChapterDOI
TL;DR: In this paper, a meta-analysis of the relationship between energy consumption and economic output was conducted, and the authors found that the role of energy prices is central to understanding the relationship.
Abstract: Energy use and economic output are positively correlated, though energy intensity has declined over time and is usually lower in richer countries than in poorer countries Numerous factors affect the energy intensity of economies, and energy efficiency is obviously one of the most important However, the rebound effect might limit the possibilities for energy efficiency improvements to reduce energy intensity Natural science suggests that energy is crucial to economic production, and ecological economists and some economic historians argue that increasing energy supply has been a principal driver of growth On the other hand, most mainstream economic growth theories ignore the role of energy These views may diverge because energy scarcity historically imposed constraints on growth, but the increased availability of modern energy sources has reduced energy’s importance as a driver of growth Empirical research on whether energy causes growth or vice versa is inconclusive, but a meta-analysis finds that the role of energy prices is central to understanding the relationship

264 citations


Posted Content
TL;DR: In this article, the extent of racial/ethnic discrimination in the largest consumer-lending market using an identification afforded by the pricing of mortgage credit risk by Fannie Mae and Freddie Mac is estimated.
Abstract: Discrimination in lending can occur either in face-to-face decisions or in algorithmic scoring. We provide a workable interpretation of the courts’ legitimate-business-necessity defense of statistical discrimination. We then estimate the extent of racial/ethnic discrimination in the largest consumer-lending market using an identification afforded by the pricing of mortgage credit risk by Fannie Mae and Freddie Mac. We find that lenders charge Latinx/African-American borrowers 7.9 and 3.6 basis points more for purchase and refinance mortgages respectively, costing them $765M in aggregate per year in extra interest. FinTech algorithms also discriminate, but 40% less than face-to-face lenders. These results are consistent with both FinTech and non-FinTech lenders extracting monopoly rents in weaker competitive environments or profiling borrowers on low-shopping behavior. Such strategic pricing is not illegal per se, but under the law, it cannot result in discrimination. The lower levels of price discrimination by algorithms suggests that removing face-to-face interactions can reduce discrimination. Further silver linings emerge in the FinTech era: (1) Discrimination is declining; algorithmic lending may have increased competition or encouraged more shopping with the ease of platform applications. (2) We find that 0.74-1.3 million minority applications were rejected between 2009 and 2015 due to discrimination; however, FinTechs do not discriminate in loan approval.

217 citations


Posted ContentDOI
TL;DR: Public attention to the power of finance and the attendant wealth that financiers are able to extract from society waxes and wanes over time, usually in conjunction with the actual evolution of the political power and its associated incomes as discussed by the authors.
Abstract: Public attention to the power of finance and the attendant wealth that financiers are able to extract from society waxes and wanes over time, usually in conjunction with the actual evolution of the political power of finance and its associated incomes.

195 citations


Book ChapterDOI
TL;DR: A review of the existing validation techniques for agent-based models in economics can be found in this paper, where the authors sketch a simple theoretical framework that conceptualizes existing validation approaches, which examine along three different dimensions: (i) comparison between artificial and real-world data; (ii) calibration and estimation of model parameters; and (iii) parameter space exploration.
Abstract: Since the survey by Windrum et al. (Journal of Artificial Societies and Social Simulation 10:8, 2007), research on empirical validation of agent-based models in economics has made substantial advances, thanks to a constant flow of high-quality contributions. This Chapter attempts to take stock of such recent literature to offer an updated critical review of the existing validation techniques. We sketch a simple theoretical framework that conceptualizes existing validation approaches, which we examine along three different dimensions: (i) comparison between artificial and real-world data; (ii) calibration and estimation of model parameters; and (iii) parameter space exploration. Finally, we discuss open issues in the field of ABM validation and estimation. In particular, we argue that more research efforts should be devoted toward advancing hypothesis testing in ABM, with specific emphasis on model stationarity and ergodicity.

194 citations


Posted Content
TL;DR: This paper analyzed the impacts of the 2018 trade war on the U.S. economy and found that tradeable-sector workers in heavily Republican counties were the most negatively affected by the trade war.
Abstract: We analyze the impacts of the 2018 trade war on the U.S. economy. We estimate import demand and export supply elasticities using changes in U.S. and retaliatory tariffs over time. Imports from targeted countries declined 31.5% within products, while targeted U.S. exports fell 11.0%. We find complete pass-through of U.S. tariffs to variety-level import prices. Using a general equilibrium framework that matches these elasticities, we compute the aggregate and regional impacts. Annual consumer and producer losses from higher costs of imports were $68.8 billion (0.37% of GDP). After accounting for higher tariff revenue and gains to domestic producers from higher prices, the aggregate welfare loss was $7.8 billion (0.04% of GDP). U.S. tariffs favored sectors located in politically competitive counties, but retaliatory tariffs offset the benefits to these counties. We find that tradeable-sector workers in heavily Republican counties were the most negatively affected by the trade war.

171 citations


Posted Content
TL;DR: The Euro Area Monetary Policy Event-Study Database (EA-MPD) as discussed by the authors was used to study the information flow from the ECB on policy dates since its inception, using tick data.
Abstract: We study the information flow from the ECB on policy dates since its inception, using tick data. We show that three factors capture about all of the variation in the yield curve but that these are different factors with different variance shares in the window that contains the policy decision announcement and the window that contains the press conference. We also show that the QE-related policy factor has been dominant in the recent period and that Forward Guidance and QE effects have been very persistent on the longer-end of the yield curve. We further show that broad and banking stock indices' responses to monetary policy surprises depended on the perceived nature of the surprises. We find no evidence of asymmetric responses of financial markets to positive and negative surprises, in contrast to the literature on asymmetric real effects of monetary policy. Lastly, we show how to implement our methodology for any policy-related news release, such as policymaker speeches. To carry out the analysis, we construct the Euro Area Monetary Policy Event- Study Database (EA-MPD). This database, which contains intraday asset price changes around the policy decision announcement as well as around the press conference, is a contribution on its own right and we expect it to be the standard in monetary policy research for the euro area.

160 citations


Posted Content
TL;DR: This article proposed and implemented a procedure to dynamically hedge climate change risk by extracting innovations from climate news series that they construct through textual analysis of newspapers and then use a mimicking portfolio approach to build climate change hedge portfolios, which yields parsimonious and industry-balanced portfolios that perform well in hedging innovations in climate news both in sample and out of sample.
Abstract: We propose and implement a procedure to dynamically hedge climate change risk. We extract innovations from climate news series that we construct through textual analysis of newspapers. We then use a mimicking portfolio approach to build climate change hedge portfolios. We discipline the exercise by using third-party ESG scores of firms to model their climate risk exposures. We show that this approach yields parsimonious and industry-balanced portfolios that perform well in hedging innovations in climate news both in sample and out of sample. We discuss multiple directions for future research on financial approaches to managing climate risk.

147 citations


ReportDOI
TL;DR: The authors developed a tractable quantitative, general equilibrium, oligopsony model of the labor market, and estimated key parameters using within-firm-state, across-market differences in wage and employment responses to state corporate tax changes in U.S. Census data.
Abstract: What are the welfare implications of labor market power? We provide an answer to this question in two steps: (1) we develop a tractable quantitative, general equilibrium, oligopsony model of the labor market, (2) we estimate key parameters using within-firm-state, across-market differences in wage and employment responses to state corporate tax changes in U.S. Census data. We validate the model against recent evidence on productivity-wage pass-through, and new measurements of the distribution of local market concentration. The model implies welfare losses from labor market power that range from 2.9 to 8.0 percent of lifetime consumption. However, despite large contemporaneous losses, labor market power has not contributed to the declining labor share. Finally, we show that minimum wages can deliver moderate, and limited, welfare gains by reallocating workers from smaller to larger, more productive firms.

146 citations


ReportDOI
TL;DR: In this paper, the authors explore the impacts of the Trump administration's trade policy on prices and welfare, and find that the full incidence of the tariff falls on domestic consumers, with a reduction in U.S. real income of $1.4 billion per month.
Abstract: This paper explores the impacts of the Trump administration’s trade policy on prices and welfare. Over the course of 2018, the U.S. experienced substantial increases in the prices of intermediates and final goods, dramatic changes to its supply-chain network, reductions in availability of imported varieties, and complete passthrough of the tariffs into domestic prices of imported goods. Overall, using standard economic methods, we find that the full incidence of the tariff falls on domestic consumers, with a reduction in U.S. real income of $1.4 billion per month by the end of 2018. We also see similar patterns for foreign countries who have retaliated against the U.S., which indicates that the trade war also reduced real income for other countries.

141 citations


Posted Content
TL;DR: This work develops an estimator for the variance-covariance matrix (VCV) of OLS and 2SLS that allows for arbitrary dependence of the errors across observations in space or network structure and across time periods and provides guidance to the applied researcher with respect to whether to include potentially correlated regressors and the choice of cluster bandwidth.
Abstract: Analyses of spatial or network data are now very common. Nevertheless, statistical inference is challenging since unobserved heterogeneity can be correlated across neighboring observational units. We develop an estimator for the variance-covariance matrix (VCV) of OLS and 2SLS that allows for arbitrary dependence of the errors across observations in space or network structure and across time periods. As a proof of concept, we conduct Monte Carlo simulations in a geospatial setting based on U.S. metropolitan areas. Tests based on our estimator of the VCV asymptotically correctly reject the null hypothesis, whereas conventional inference methods, e.g., those without clusters or with clusters based on administrative units, reject the null hypothesis too often. We also provide simulations in a network setting based on the IDEAS structure of coauthorship and real-life data on scientific performance. The Monte Carlo results again show that our estimator yields inference at the correct significance level even in moderately sized samples and that it dominates other commonly used approaches to inference in networks. We provide guidance to the applied researcher with respect to (i) whether or not to include potentially correlated regressors and (ii) the choice of cluster bandwidth. Finally, we provide a companion statistical package (acreg) enabling users to adjust the OLS and 2SLS coefficient's standard errors to account for arbitrary dependence.

ReportDOI
TL;DR: The authors showed that the macroeconomic effect of health is quantitatively close to that found by aggregating the microeconomic effects, controlling for potential spillovers of population health at the aggregate level.
Abstract: Micro-based and macro-based approaches have been used to assess the effects of health on economic growth. Micro-based approaches aggregate the return on individual health from Mincerian wage regressions to derive the macroeconomic effects of population health. Macro-based approaches estimate a generalized aggregate production function that decomposes output into its components. The microbased approach tends to find smaller effects than the macro-based approach, thus presenting a micromacro puzzle regarding the economic return on health. We reconcile these two strands of literature by showing that the point estimate of the macroeconomic effect of health is quantitatively close to that found by aggregating the microeconomic effects, controlling for potential spillovers of population health at the aggregate level. Our results justify using the micro-based approach to estimate the direct economic benefits of health interventions.


Posted Content
TL;DR: This article studied the long-term impact of climate change on economic activity across countries, using a stochastic growth model where labour productivity is affected by country-specific climate variables -defined as deviations of temperature and precipitation from their historical norms.
Abstract: We study the long-term impact of climate change on economic activity across countries, using a stochastic growth model where labour productivity is affected by country-specific climate variables - defined as deviations of temperature and precipitation from their historical norms. Using a panel data set of 174 countries over the years 1960 to 2014, we find that per-capita real output growth is adversely affected by persistent changes in the temperature above or below its historical norm, but we do not obtain any statistically significant effects for changes in precipitation. Our counterfactual analysis suggests that a persistent increase in average global temperature by 0.04oC per year, in the absence of mitigation policies, reduces world real GDP per capita by 7.22 percent by 2100. On the other hand, abiding by the Paris Agreement, thereby limiting the temperature increase to 0.01oC per annum, reduces the loss substantially to 1.07 percent. These effects vary significantly across countries. We also provide supplementary evidence using data on a sample of 48 U.S. states between 1963 and 2016, and show that climate change has a long-lasting adverse impact on real output in various states and economic sectors, and on labour productivity and employment.

Posted Content
TL;DR: A review of the recent literature on the dynamics of global wealth inequality can be found in this paper, where the authors reconcile available estimates of wealth inequality in the United States and discuss how new data sources (leaks from financial institutions, tax amnesties, and macroeconomic statistics of tax havens) can be leveraged to better capture the wealth of the rich.
Abstract: This article reviews the recent literature on the dynamics of global wealth inequality. I first reconcile available estimates of wealth inequality in the United States. Both surveys and tax data show that wealth inequality has increased dramatically since the 1980s, with a top 1% wealth share around 40% in 2016 vs. 25–30% in the 1980s. Second, I discuss the fast growing literature on wealth inequality across the world. Evidence points towards a rise in global wealth concentration: for China, Europe, and the United States combined, the top 1% wealth share has increased from 28% in 1980 to 33% today, while the bottom 75% share hovered around 10%. Recent studies, however, may under-estimate the level and rise of inequality, as financial globalization makes it increasingly hard to measure wealth at the top. I discuss how new data sources (leaks from financial institutions, tax amnesties, and macroeconomic statistics of tax havens) can be leveraged to better capture the wealth of the rich.

Posted Content
TL;DR: This study proposes a computational intelligence technique that uses a hybrid Neuro-Fuzzy controller, namely PATSOS, to forecast the direction in the change of the daily price of Bitcoin, which outperforms two other computational intelligence models.
Abstract: Cryptocurrencies, with Bitcoin being the most notable example, have attracted considerable attention in recent years, and they have experienced large fluctuations in their price. While a few studies employ conventional statistical and econometric approaches to reveal the driving factors of Bitcoin's prices, research on the development of forecasting models to be used as decision support tools in investment strategies is scarce. This study proposes a computational intelligence technique that uses a hybrid Neuro-Fuzzy controller, namely PATSOS, to forecast the direction in the change of the daily price of Bitcoin. The proposed methodology outperforms two other computational intelligence models, the first being developed with a simpler neuro-fuzzy approach, and the second being developed with artificial neural networks. Furthermore, the investment returns achieved by a trading simulation, based on the signals of the proposed model, are 71.21% higher than the ones achieved through a naive buy-and-hold strategy. The performance of the PATSOS system is robust to the use of other cryptocurrencies. (This abstract was borrowed from another version of this item.)

Posted Content
TL;DR: In this article, the optimal design of a central bank digital currency (CBDC) in an environment where agents sort into cash, CBDC and bank deposits according to their preferences over anonymity and security was studied.
Abstract: We study the optimal design of a central bank digital currency (CBDC) in an environment where agents sort into cash, CBDC and bank deposits according to their preferences over anonymity and security; and where network effects make the convenience of payment instruments dependent on the number of their users. CBDC can be designed with attributes similar to cash or deposits, and can be interest-bearing: a CBDC that closely competes with deposits depresses bank credit and output, while a cash-like CBDC may lead to the disappearance of cash. Then, the optimal CBDC design trades off bank intermediation against the social value of maintaining diverse payment instruments. When network effects matter, an interest-bearing CBDC alleviates the central bank's tradeoff.

Posted Content
TL;DR: In this paper, the authors conceptualized an original theoretical model to show, using the competing value model (CVM), how big data analytics capability (BDAC) under a moderating influence of organizational culture, affects swift trust (ST) and collaborative performance (CP).
Abstract: The main objective of the study is to understand how big data analytics capability (BDAC) as an organizational culture can enhance trust and collaborative performance between civil and military organizations engaged in disaster relief operations. The theoretical framework is grounded in organizational information processing theory (OIPT). We have conceptualized an original theoretical model to show, using the competing value model (CVM), how BDAC, under a moderating influence of organizational culture, affects swift trust (ST) and collaborative performance (CP). We used WarpPLS 6.0 to test the proposed research hypotheses using multi-respondent data gathered through an email questionnaire sent to managers working in 373 organizations, including the military forces of different countries, government aid agencies, UN specialized agencies, international non-government organizations (NGOs), service providers, and contractors. The results offer four important implications. First, BDAC has a positive, significant effect on ST and CP. Second, flexible orientation (FO) and controlled orientation (CO) have no significant influence on building ST. Third, FO has a positive and significant moderating effect on the path joining BDAC and CP. Finally, CO has negative and significant moderating effect on the path joining BDAC and CP. The control variables: temporal orientation (TO) and interdependency (I) have significant effects on ST and CP. These results extend OIPT to create a better understanding of the application of information processing capabilities to build swift trust and improve collaborative performance. Furthermore, managers can derive multiple insights from this theoretically-grounded study to understand how BDAC can be exploited to gain insights in contexts of different management styles and cultures. We have also outlined the study limitations and provided numerous future research directions. (This abstract was borrowed from another version of this item.)


Posted Content
TL;DR: The following main results are derived: first, event study designs and distributed-lag models are numerically identical leading to the same parameter estimates after correct reparametrization, and second, binning of effect window endpoints allows identification of dynamic treatment effects even when no never-treated units are present.
Abstract: We discuss important features and pitfalls of panel-data event study designs. We derive the following main results: First, event study designs and distributed-lag models are numerically identical leading to the same parameter estimates after correct reparametrization. Second, binning of effect window endpoints allows identification of dynamic treatment effects even when no never-treated units are present. Third, classic dummy variable event study designs can be naturally generalized to models that account for multiple events of different sign and intensity of the treatment, which are particularly interesting for research in labor economics and public finance.

Report SeriesDOI
TL;DR: In this paper, the authors study how the introduction of a central bank-issued digital currency affects interest rates, the level of economic activity, and welfare in an environment where both central bank money and private bank deposits are used in exchange.
Abstract: We study how the introduction of a central bank-issued digital currency affects interest rates, the level of economic activity, and welfare in an environment where both central bank money and private bank deposits are used in exchange. Banks in our model are financially constrained, and the liquidity premium on bank deposits affects the level of aggregate investment. We study the optimal design of a digital currency in this setting, including whether it should pay interest and how widely it should circulate. We highlight an important policy tradeoff: while a digital currency tends to promote efficiency in exchange, it can also crowd out bank deposits, raise banksfunding costs, and decrease investment. Despite these effects, introducing a central bank digital currency often raises welfare.

Posted Content
TL;DR: The authors analyzed the narratives of 51 role model women entrepreneurs to explore how they represent women entrepreneurs and entrepreneurship and found that in accordance with the contemporary pressure for women to succeed and perform personally and professionally, the voice of the (super)woman doing "individualized entrepreneurial femininity" dominates.
Abstract: It is suggested that more "role model" women entrepreneurs are needed. However, the gender gap in entrepreneurship remains. This study analyses the narratives of 51 role model women entrepreneurs to explore how they represent women entrepreneurs and entrepreneurship. We found that in accordance with the contemporary pressure for women to succeed and perform personally and professionally, the voice of the (super)woman doing "individualized entrepreneurial femininity" dominates. The role models narratives obscure race, class, and age barriers; reproduce prevailing gender stereotypes; normalize discriminatory workplace treatment and depict entrepreneurship as an appropriate alternative for working mothers. Implications for policy makers are presented.

Posted Content
TL;DR: The authors proposed a model selection method to systematically evaluate the contribution to asset pricing of any new factor, above and beyond what a high-dimensional set of existing factors explains, by explicitly accounting for potential model-selection mistakes.
Abstract: We propose a model-selection method to systematically evaluate the contribution to asset pricing of any new factor, above and beyond what a high-dimensional set of existing factors explains. Our methodology explicitly accounts for potential model-selection mistakes, unlike the standard approaches that assume perfect variable selection, which rarely occurs in practice and produces a bias due to the omitted variables. We apply our procedure to a set of factors recently discovered in the literature. While most of these new factors are found to be redundant relative to the existing factors, a few — such as profitability — have statistically significant explanatory power beyond the hundreds of factors proposed in the past. In addition, we show that our estimates and their significance are stable, whereas the model selected by simple LASSO is not.

Report SeriesDOI
TL;DR: In this article, the EU-OECD method is used to define functional urban areas (FUAs), which encompass the economic and functional extent of cities based on daily people's movements.
Abstract: This paper describes the EU-OECD method to define functional urban areas (FUAs). Being composed of a city and its commuting zone, FUAs encompass the economic and functional extent of cities based on daily people’s movements. The paper first presents briefly the methodological approach and subsequently provides a detailed description of the identification algorithm, together with the data needed to apply it. This definition has been applied to 33 OECD member countries and Colombia, as well as to all European Union member countries.

Posted Content
TL;DR: In this article, a comprehensive review of the circular economy concept in developing country context is provided, and a novel model is proposed by adopting Fuzzy Analytics Network Process (FANP) to quantify the priority weights of the sustainability indicators to provide guidelines for the industry stakeholders at different stages of industry cycle to transition toward the Circular economy.
Abstract: The concept of the circular economy has gained well-recognition across the world for the past decades. With the heightening risk of the impact of climate change, resource scarcity to meet the increasing world population, the need to transition to a more sustainable development model is urgent. The circular economy is often cited as one of the best solutions to support sustainable development. However, the diffusion of this concept in the industrial arena is still relatively slow, particularly in the developing country, which collectively exerts high potential to be the world’s largest economies and workforce. It is crucial to make sure that the development of these nations is sustainable and not bearing on the cost of future generation. Thus, this work aims to provide a comprehensive review of the circular economy concept in developing country context. Furthermore, a novel model is proposed by adopting Fuzzy Analytics Network Process (FANP) to quantify the priority weights of the sustainability indicators to provide guidelines for the industry stakeholders at different stages of industry cycle to transition toward the circular economy. The results revealed that improvement in economic performance and public acceptance are they key triggers to encourage stakeholders for sustainable development. The outcomes serve as a reference to enhance the overall decision-making process of industry stakeholders. Local authorities can adopt the recommendations to design policy and incentive that encourage the adoption of circular economy in real industry operation to spur up economic development, without neglecting environmental well-being and jeopardizing social benefits.

BookDOI
TL;DR: A new generation of infrastructure projects that harness the power of nature can help achieve development goals, including water security and climate resilience as discussed by the authors, which can produce lower cost and more resilient services.
Abstract: A new generation of infrastructure projects that harness the power of nature can help achieve development goals, including water security and climate resilience. In this report from the World Bank and World Resources Institute, both organizations are calling for green infrastructure, such as mangroves and wetlands, to play a bigger role in traditional infrastructure planning. Integrating nature into mainstream infrastructure systems can produce lower cost and more resilient services. This report guides developing country service providers and their partners on how to seize this opportunity. It reviews approaches and examples of how to integrate green infrastructure into mainstream project appraisal processes and investments.

ReportDOI
TL;DR: In this article, the authors discuss the potential for digital currencies associated with large platform ecosystems to lead to a re-bundling of money in which payment services are packaged with an array of data services, encouraging differentiation but discouraging interoperability between platforms.
Abstract: The ongoing digital revolution may lead to a radical departure from the traditional model of monetary exchange. We may see an unbundling of the separate roles of money, creating fiercer competition among specialized currencies. On the other hand, digital currencies associated with large platform ecosystems may lead to a re-bundling of money in which payment services are packaged with an array of data services, encouraging differentiation but discouraging interoperability between platforms. Digital currencies may also cause an upheaval of the international monetary system: countries that are socially or digitally integrated with their neighbors may face digital dollarization, and the prevalence of systemically important platforms could lead to the emergence of digital currency areas that transcend national borders. Central bank digital currency (CBDC) ensures that public money remains a relevant unit of account.

Posted Content
TL;DR: In this paper, the authors examined companies' financial and environmental performance following the issuance of green bonds, finding that the stock market responds positively to the announcement of green bond issues, suggesting that green bonds are effective in improving companies' environmental footprint.
Abstract: This paper studies green bonds, a relatively new instrument in sustainable finance. I first describe the market for green bonds and characterize the “green bond boom” witnessed in recent years. Second, using firm-level data on green bonds issued by public companies, I examine companies’ financial and environmental performance following the issuance of green bonds. I find that the stock market responds positively to the announcement of green bond issues. Moreover, I document a significant increase in environmental performance, suggesting that green bonds are effective in improving companies’ environmental footprint. These findings are only significant for green bonds that are certified by independent third parties, suggesting that certification is an important governance mechanism in the green bond market. I conclude by discussing potential implications for public policy.

ReportDOI
TL;DR: This paper found evidence for smaller negative between-firm effects as more productive, internationally exposed, first have been more negatively impacted than less productive domestic firms, and the Brexit process is estimated to have reduced UK productivity by between 2% and 5% over the three years after the referendum.
Abstract: We use a major new survey of UK firms, the Decision Maker Panel, to assess the impact of the June 2016 Brexit referendum. We identify three key results. First, the UK’s decision to leave the EU has generated a large, broad and long-lasting increase in uncertainty. Second, anticipation of Brexit is estimated to have gradually reduced investment by about 11% over the three years following the June 2016 vote. This fall in investment took longer to occur than predicted at the time of the referendum, suggesting that the size and persistence of this uncertainty may have delayed firms’ response to the Brexit vote. Finally, the Brexit process is estimated to have reduced UK productivity by between 2% and 5% over the three years after the referendum. Much of this drop is from negative within-firm effects, in part because firms are committing several hours per week of top-management time to Brexit planning. We also find evidence for smaller negative between-firm effects as more productive, internationally exposed, first have been more negatively impacted than less productive domestic firms.

ReportDOI
TL;DR: In this paper, the authors construct a macro-model with a banking sector that links together policy rates, deposit rates, and lending rates and show that negative policy rates reduce bank profits and the total effect on aggregate output can be contractionary.
Abstract: Following the crisis of 2008, several central banks engaged in a new experiment by setting negative policy rates. Using aggregate and bank level data, we document that deposit rates stopped responding to policy rates once they went negative and that bank lending rates in some cases increased rather than decreased in response to policy rate cuts. Based on the empirical evidence, we construct a macro-model with a banking sector that links together policy rates, deposit rates and lending rates. Once the policy rate turns negative, the usual transmission mechanism of monetary policy through the bank sector breaks down. Moreover, because a negative policy rate reduces bank profits, the total effect on aggregate output can be contractionary. A calibration which matches Swedish bank level data suggests that a policy rate of -0.50 percent increases borrowing rates by 15 basis points and reduces output by 7 basis points.