{"title":"Defragmenting Markets: Evidence from Agency MBS","authors":"Haoyang Liu, Zhaogang Song, J. Vickery","doi":"10.2139/ssrn.3838913","DOIUrl":"https://doi.org/10.2139/ssrn.3838913","url":null,"abstract":"Agency mortgage-backed securities (MBS) issued by Fannie Mae and Freddie Mac have historically traded in separate forward markets. We study the consequences of this fragmentation, showing that market liquidity endogenously concentrated in Fannie Mae MBS, leading to higher issuance and trading volume, lower transaction costs, higher security prices, and a lower primary market cost of capital for Fannie Mae. We then analyze a change in market design—the Single Security Initiative—which consolidated Fannie Mae and Freddie Mac MBS trading into a single market in June 2019. We find that consolidation increased the liquidity and prices of Freddie Mac MBS without measurably reducing liquidity for Fannie Mae; this was in part achieved by aligning characteristics of the underlying MBS pools issued by the two agencies. Prices partially converged prior to the consolidation event, in anticipation of future liquidity. Consolidation increased Freddie Mac’s fee income by enabling it to remove discounts that previously compensated loan sellers for lower liquidity.","PeriodicalId":314858,"journal":{"name":"Federal Reserve Bank of New York Research Paper Series","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122203963","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}
{"title":"Combinatorial Growth with Physical Constraints: Evidence from Electronic Miniaturization","authors":"Pablo Azar","doi":"10.2139/ssrn.3853184","DOIUrl":"https://doi.org/10.2139/ssrn.3853184","url":null,"abstract":"In the past sixty years, transistor sizes and weights have decreased by 50 percent every eighteen months, following Moore’s Law. Smaller and lighter electronics have increased productivity in virtually every industry and spurred the creation of entirely new sectors of the economy. However, while the effect of the increasing quality of computers and electronics on GDP has been widely studied, the question of how electronic miniaturization affects economic growth has been unexplored. To quantify the effect of electronic miniaturization on GDP, this paper builds an economic growth model that incorporates physical constraints on firms’ production sets. This model allows for new types of productivity spillovers that are driven by products’ physical characteristics. Not only are there spillovers from changes in industry productivity, but also, there can be “size spillovers,” where the miniaturization of one industry’s product leads to miniaturization of products that are downstream in the supply chain, reflecting how transistor miniaturization has led to the decrease in size of a large variety of electronic products. Using a new data set of product weights and sizes, we test the predictions of the model and show that Moore’s Law accounts for approximately 3.5 percent of all productivity growth in the 1982-2007 period, and for 37.5 percent of the productivity growth in heavy manufacturing industries. The results are robust under multiple specifications, and increase in strength during the 1997-2007 subperiod.","PeriodicalId":314858,"journal":{"name":"Federal Reserve Bank of New York Research Paper Series","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115871694","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}
{"title":"U.S. Market Concentration and Import Competition","authors":"M. Amiti, S. Heise","doi":"10.2139/ssrn.3847929","DOIUrl":"https://doi.org/10.2139/ssrn.3847929","url":null,"abstract":"A rapidly growing literature has shown that market concentration among domestic firms has increased in the United States over the last three decades. Using confidential census data for the manufacturing sector, we show that typical measures of concentration, once adjusted for sales by foreign exporters, actually stayed constant between 1992 and 2012. We reconcile these findings by linking part of the increase in domestic concentration to import competition. Although concentration among U.S.-based firms rose, the growth of foreign firms, mostly at the bottom of the sales distribution, counteracted this increase. We find that higher import competition caused a decline in the market shares of the top twenty U.S. firms.","PeriodicalId":314858,"journal":{"name":"Federal Reserve Bank of New York Research Paper Series","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128647643","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}
{"title":"The Law of One Price in Equity Volatility Markets","authors":"Peter Van Tassel","doi":"10.2139/ssrn.3751612","DOIUrl":"https://doi.org/10.2139/ssrn.3751612","url":null,"abstract":"This paper documents law of one price violations in equity volatility markets. While tightly linked by no-arbitrage restrictions, the prices of VIX futures exhibit significant deviations relative to their option-implied upper bounds. Static arbitrage opportunities occur when the prices of VIX futures violate their bounds. The deviations widen during periods of market stress and predict the returns of VIX futures. A relative value trading strategy based on the deviation measure earns a large Sharpe ratio and economically significant alpha-to-margin. There is evidence that systematic risk and demand pressure contribute to the variation in the no-arbitrage deviations over time.","PeriodicalId":314858,"journal":{"name":"Federal Reserve Bank of New York Research Paper Series","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116321677","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}
{"title":"High Frequency Data and a Weekly Economic Index during the Pandemic","authors":"D. Lewis, Karel Mertens, J. Stock, Mihir Trivedi","doi":"10.2139/ssrn.3751616","DOIUrl":"https://doi.org/10.2139/ssrn.3751616","url":null,"abstract":"This paper describes a weekly economic index (WEI) developed to track the rapid economic developments associated with the onset of and policy response to the novel coronavirus in the United States. The WEI, with its ten component series, tracks the overall economy. Comparing the contributions of the WEI's components in the 2008 and 2020 recessions reveals differences in how the two events played out at a high frequency. During the 2020 collapse and recovery, it provides a benchmark to interpret similarities and differences of novel indicators with shorter samples and/or nonstationary coverage, such as mobility indexes or credit card spending.","PeriodicalId":314858,"journal":{"name":"Federal Reserve Bank of New York Research Paper Series","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131487650","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}
{"title":"Bank Capital and Real GDP Growth","authors":"Nina Boyarchenko, D. Giannone, A. Kovner","doi":"10.2139/ssrn.3742961","DOIUrl":"https://doi.org/10.2139/ssrn.3742961","url":null,"abstract":"We study the relationship between bank capital ratios and the distribution of future real GDP growth. Growth in the aggregate bank capital ratio corresponds to a smaller left tail of GDP—smaller crisis probability—but at the cost of a smaller right tail of growth outcomes—smaller probability of exuberant growth. This trade-off persists at horizons of up to eight quarters, highlighting the long-range consequences of changes in bank capital. We show that the predictive information in bank capital ratio growth is over and above that contained in real credit growth, suggesting importance for bank capital beyond supplying credit to the nonfinancial sector. Our results suggest that coordination between macroprudential and monetary policy is crucial for supporting stable growth.","PeriodicalId":314858,"journal":{"name":"Federal Reserve Bank of New York Research Paper Series","volume":"650 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132021137","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}
Ozge Akinci, Gianluca Benigno, Marco Del Negro, A. Queraltó
{"title":"The Financial (In)Stability Real Interest Rate, R**","authors":"Ozge Akinci, Gianluca Benigno, Marco Del Negro, A. Queraltó","doi":"10.2139/ssrn.3727406","DOIUrl":"https://doi.org/10.2139/ssrn.3727406","url":null,"abstract":"We introduce the concept of financial stability real interest rate using a macroeconomic banking model with an occasionally binding financing constraint as in Gertler and Kiyotaki (2010). The financial stability interest rate, r**, is the threshold interest rate that triggers the constraint being binding. Increasing imbalances in the financial sector measured by an increase in leverage are accom- panied by a lower threshold that could trigger financial instability events. We also construct a theoretical implied financial condition index and show how it is related to the gap between the natural and financial stability interest rates.","PeriodicalId":314858,"journal":{"name":"Federal Reserve Bank of New York Research Paper Series","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133763976","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}
{"title":"COVID Response: The Primary Dealer Credit Facility","authors":"Antoine Martin, S. McLaughlin","doi":"10.2139/ssrn.3931595","DOIUrl":"https://doi.org/10.2139/ssrn.3931595","url":null,"abstract":"On March 17, 2020, the Federal Reserve announced that it would re-establish the Primary Dealer Credit Facility (PDCF) to allow primary dealers to support smooth market functioning and facilitate the availability of credit to businesses and households. The PDCF started offering overnight and term funding with maturities of up to ninety days on March 20. It will be in place for at least six months and may be extended as conditions warrant. In this post, we provide an overview of the PDCF and its usage to date.","PeriodicalId":314858,"journal":{"name":"Federal Reserve Bank of New York Research Paper Series","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128775756","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}
{"title":"The Effect of Bank Monitoring on Loan Repayment","authors":"Nicola Branzoli, Fulvia Fringuellotti","doi":"10.2139/ssrn.3601944","DOIUrl":"https://doi.org/10.2139/ssrn.3601944","url":null,"abstract":"Monitoring is one of the main activities explaining the existence of banks, yet empirical evidence about its effect on loan outcomes is scant. Using granular loan-level information from the Italian Credit Register, we build a novel measure of bank monitoring based on banks’ requests for information on their existing borrowers and we investigate the effect of bank monitoring on loan repayment. We perform a causal analysis exploiting changes in the regional corporate tax rate as a source of exogenous variation in bank monitoring. Our identification strategy is supported by a theoretical model predicting that a decrease in the tax rate improves bank incentives to monitor borrowers by increasing returns from lending. We find that bank monitoring reduces the probability of a delinquency in a substantial way and that the effect is stronger for the types of loans that benefit most from bank oversight, such as term loans.","PeriodicalId":314858,"journal":{"name":"Federal Reserve Bank of New York Research Paper Series","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116058460","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}
{"title":"Liquidity and Volatility in the U.S. Treasury Market","authors":"Giang Nguyen, R. Engle, M. Fleming, Eric Ghysels","doi":"10.2139/ssrn.2195655","DOIUrl":"https://doi.org/10.2139/ssrn.2195655","url":null,"abstract":"We model the joint dynamics of intraday liquidity, volume, and volatility in the U.S. Treasury market, especially through the 2007–09 financial crisis and around important economic announcements. Using various specifications based on Bauwens and Giot (2000)’s Log-ACD(1,1) model, we find that liquidity, volume, and volatility are highly persistent, with volatility having a lower short-term persistence than the other two. Market liquidity and volume are important to explaining volatility dynamics but not vice versa. In addition, market dynamics change during the financial crisis, with all variables exhibiting increased responsiveness to their most recent realizations. Our models also reveal different market dynamics around announcements. Finally, we introduce new measures of liquidity risk that are useful for continually monitoring liquidity conditions and the risk of liquidity stress in the market.","PeriodicalId":314858,"journal":{"name":"Federal Reserve Bank of New York Research Paper Series","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129494883","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}