Traditionally, aggregate liquidity shocks are modelled as exogenous events. Extending our previous work (Cao & Illing, 2007), this paper analyses the adequate policy response to endogenous systemic liquidity risk. We analyse the feedback between lender of last resort policy and incentives of private banks, determining the aggregate amount of liquidity available. We show that imposing minimum liquidity standards for banks ex ante are a crucial requirement for sensible lender of last resort policy. In addition, we analyse the impact of equity requirements and narrow banking, in the sense that banks are required to hold sufficient liquid funds so as to pay out in all contingencies. We show that such a policy is strictly inferior to imposing minimum liquidity standards ex ante combined with lender of last resort policy.
{"title":"Endogenous Systemic Liquidity Risk","authors":"Jin Cao, G. Illing","doi":"10.5282/UBM/EPUB.3358","DOIUrl":"https://doi.org/10.5282/UBM/EPUB.3358","url":null,"abstract":"Traditionally, aggregate liquidity shocks are modelled as exogenous events. Extending our previous work (Cao & Illing, 2007), this paper analyses the adequate policy response to endogenous systemic liquidity risk. We analyse the feedback between lender of last resort policy and incentives of private banks, determining the aggregate amount of liquidity available. We show that imposing minimum liquidity standards for banks ex ante are a crucial requirement for sensible lender of last resort policy. In addition, we analyse the impact of equity requirements and narrow banking, in the sense that banks are required to hold sufficient liquid funds so as to pay out in all contingencies. We show that such a policy is strictly inferior to imposing minimum liquidity standards ex ante combined with lender of last resort policy.","PeriodicalId":179699,"journal":{"name":"CESifo: Monetary Policy & International Finance (Topic)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2008-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127201900","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}
The money-age distribution is hump-shaped for the US post-war economy. There is no clear cut relation between the variation of money holdings within generations and age. Furthermore, money is found to be only weakly correlated with both income and wealth. We analyze three motives for money demand in an overlapping generations model in order to explain these observations: 1) money in the utility, 2) an economy with costly credit service, and 3) limited participation. All three models are consistent with the hump-shaped relation between average money holdings and age, yet they predict a much closer association between money holdings, income, wealth, and age than we find in the data. Only the limited-participation model partly replicates the low bivariate correlation between money and income as well as between money and interest bearing assets. None of the three models satisfactorily explains these stylized facts.
{"title":"The Money-Age Distribution: Empirical Facts and Limited Monetary Models","authors":"B. Heer, Alfred Maussner, P. McNelis","doi":"10.2139/ssrn.965397","DOIUrl":"https://doi.org/10.2139/ssrn.965397","url":null,"abstract":"The money-age distribution is hump-shaped for the US post-war economy. There is no clear cut relation between the variation of money holdings within generations and age. Furthermore, money is found to be only weakly correlated with both income and wealth. We analyze three motives for money demand in an overlapping generations model in order to explain these observations: 1) money in the utility, 2) an economy with costly credit service, and 3) limited participation. All three models are consistent with the hump-shaped relation between average money holdings and age, yet they predict a much closer association between money holdings, income, wealth, and age than we find in the data. Only the limited-participation model partly replicates the low bivariate correlation between money and income as well as between money and interest bearing assets. None of the three models satisfactorily explains these stylized facts.","PeriodicalId":179699,"journal":{"name":"CESifo: Monetary Policy & International Finance (Topic)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2007-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133514389","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}
In the paper we analyze determinants of the capital market beta risk in Poland in the monthly period 1996-2002. The beta risk is measured as a time-varying parameter estimated in a regression of the Warsaw stock indexes (WIG and WIG20 separately) on major foreign stock market indexes (DJIA, NASDAQ, DAX and FTSE). The individual monthly beta parameters time series are computed as structural regression parameters estimated for daily data in monthly sub-periods in regressions for WIG and WIG20 indexes on individual foreign stock market indexes. The beta risk is an average of monthly individual beta parameters. We put forward a hypothesis that the estimated beta risk depends on monetary and real variables expressing the economic performance of the Polish economy. Hence, we build monetary and real factors models. As explanatory variables of risk, we examine: income, productivity, trade balance, budget deficit, interest rate and the zloty exchange rate. The risk factors are expressed as differentials relative to the world economy for which stands the U.S. economy. According to Fair and Shiller (1990), we test for relative one-period-ahead predictive performance of monetary and real factors models of capital market risk in Poland in the period 1999-2002. We find that monetary variables as exchange rate and interest rate have relatively more power than real variables in explaining the beta market risk in Poland.
{"title":"Determinants of Country Beta Risk in Poland","authors":"P. Wdowiński","doi":"10.2139/ssrn.510962","DOIUrl":"https://doi.org/10.2139/ssrn.510962","url":null,"abstract":"In the paper we analyze determinants of the capital market beta risk in Poland in the monthly period 1996-2002. The beta risk is measured as a time-varying parameter estimated in a regression of the Warsaw stock indexes (WIG and WIG20 separately) on major foreign stock market indexes (DJIA, NASDAQ, DAX and FTSE). The individual monthly beta parameters time series are computed as structural regression parameters estimated for daily data in monthly sub-periods in regressions for WIG and WIG20 indexes on individual foreign stock market indexes. The beta risk is an average of monthly individual beta parameters. We put forward a hypothesis that the estimated beta risk depends on monetary and real variables expressing the economic performance of the Polish economy. Hence, we build monetary and real factors models. As explanatory variables of risk, we examine: income, productivity, trade balance, budget deficit, interest rate and the zloty exchange rate. The risk factors are expressed as differentials relative to the world economy for which stands the U.S. economy. According to Fair and Shiller (1990), we test for relative one-period-ahead predictive performance of monetary and real factors models of capital market risk in Poland in the period 1999-2002. We find that monetary variables as exchange rate and interest rate have relatively more power than real variables in explaining the beta market risk in Poland.","PeriodicalId":179699,"journal":{"name":"CESifo: Monetary Policy & International Finance (Topic)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2004-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121446866","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 examine financial intermediation when banks can offer deposit or loan contracts contingent on macroeconomic shocks. We show that the risk allocation is efficient if there is no workout of banking crises. In this case, banks will shift part of the risk to depositors. In contrast, under a workout of banking crises, depositors receive non-contingent contracts with high interest rates while entrepreneurs obtain loan contracts that demand a high repayment in good times and little in bad times. As a result, the present generation overinvests and banks create large macroeconomic risks for future generations, even if the underlying risk is small or zero. This provides a new justification for capital requirements.
{"title":"Financial Intermediation and the Creation of Macroeconomic Risks","authors":"H. Gersbach","doi":"10.2139/ssrn.310547","DOIUrl":"https://doi.org/10.2139/ssrn.310547","url":null,"abstract":"We examine financial intermediation when banks can offer deposit or loan contracts contingent on macroeconomic shocks. We show that the risk allocation is efficient if there is no workout of banking crises. In this case, banks will shift part of the risk to depositors. In contrast, under a workout of banking crises, depositors receive non-contingent contracts with high interest rates while entrepreneurs obtain loan contracts that demand a high repayment in good times and little in bad times. As a result, the present generation overinvests and banks create large macroeconomic risks for future generations, even if the underlying risk is small or zero. This provides a new justification for capital requirements.","PeriodicalId":179699,"journal":{"name":"CESifo: Monetary Policy & International Finance (Topic)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2002-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132649278","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}
In this article, we shed more light on the covariances versus characteristics debate by investigating the explanatory power of the instrumented principal component analysis (IPCA), recently proposed by Kelly et al. (2019). They conclude that characteristics are covariances because there is no residual return predictability from characteristics above and beyond that in factor loadings. Our findings indicate that there is no residual return predictability from factor loadings above and beyond that in characteristics either. In particular, we find that stock returns are best explained by characteristics (characteristics are characteristics) and that a one-factor IPCA model is sufficient to explain stock risk (characteristics are covariances). We therefore conclude that characteristics are covariances or characteristics, depending on whether the goal is to explain stock returns or risk.
{"title":"Are Characteristics Covariances or Characteristics?","authors":"Lars Hornuf, C. Fieberg","doi":"10.2139/ssrn.3633662","DOIUrl":"https://doi.org/10.2139/ssrn.3633662","url":null,"abstract":"In this article, we shed more light on the covariances versus characteristics debate by investigating the explanatory power of the instrumented principal component analysis (IPCA), recently proposed by Kelly et al. (2019). They conclude that characteristics are covariances because there is no residual return predictability from characteristics above and beyond that in factor loadings. Our findings indicate that there is no residual return predictability from factor loadings above and beyond that in characteristics either. In particular, we find that stock returns are best explained by characteristics (characteristics are characteristics) and that a one-factor IPCA model is sufficient to explain stock risk (characteristics are covariances). We therefore conclude that characteristics are covariances or characteristics, depending on whether the goal is to explain stock returns or risk.","PeriodicalId":179699,"journal":{"name":"CESifo: Monetary Policy & International Finance (Topic)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128926674","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 the impact of increases in uncertainty on bank credit conditions depends on the level of uncertainty. Using firm-level survey data, we document that a surge in business-specific uncertainty is particularly damaging when this uncertainty is low: low levels nearly triple the effect compared to high levels. The result is robust to controlling for recessionary periods. To provide an interpretation, we build and calibrate a stylized model in which bank lending is governed by expectations about the future level of business uncertainty. Increases in uncertainty serve as a signal to update these expectations. The model predicts that expectations are revised more strongly and, thus, lending drops more under low uncertainty.
{"title":"Increasing Business Uncertainty and Credit Conditions in Times of Low and High Uncertainty: Evidence from Firm-Level Survey Data","authors":"C. Grimme, Steffen R. Henzel","doi":"10.2139/ssrn.3754682","DOIUrl":"https://doi.org/10.2139/ssrn.3754682","url":null,"abstract":"We demonstrate that the impact of increases in uncertainty on bank credit conditions depends on the level of uncertainty. Using firm-level survey data, we document that a surge in business-specific uncertainty is particularly damaging when this uncertainty is low: low levels nearly triple the effect compared to high levels. The result is robust to controlling for recessionary periods. To provide an interpretation, we build and calibrate a stylized model in which bank lending is governed by expectations about the future level of business uncertainty. Increases in uncertainty serve as a signal to update these expectations. The model predicts that expectations are revised more strongly and, thus, lending drops more under low uncertainty.","PeriodicalId":179699,"journal":{"name":"CESifo: Monetary Policy & International Finance (Topic)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114317847","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 introduces a new test of the predictive performance and market timing for categorical forecasts based on contingency tables when the user has non-categorical loss functions. For example, a user might be interested in the return of an underlying variable instead of just the direction. This new test statistic can also be used to determine whether directional forecasts are derived from non-directional forecasts and whether point forecast have predictive value when transformed into directional forecasts. The tests are applied to the categorical exchange rate forecasts in the ifo-Institute's World Economic Survey and to the point forecasts for quarterly GDP in the Philadelphia Fed's Survey of Professional Forecasters. We find that the loss function matters as exchange rate forecasters perform better under non-categorical loss functions, and the GDP forecasts have value up to two quarters ahead.
{"title":"Categorical Forecasts and Non-Categorical Loss Functions","authors":"C. Bürgi, Dorine Boumans","doi":"10.2139/ssrn.3598751","DOIUrl":"https://doi.org/10.2139/ssrn.3598751","url":null,"abstract":"This paper introduces a new test of the predictive performance and market timing for categorical forecasts based on contingency tables when the user has non-categorical loss functions. For example, a user might be interested in the return of an underlying variable instead of just the direction. This new test statistic can also be used to determine whether directional forecasts are derived from non-directional forecasts and whether point forecast have predictive value when transformed into directional forecasts. The tests are applied to the categorical exchange rate forecasts in the ifo-Institute's World Economic Survey and to the point forecasts for quarterly GDP in the Philadelphia Fed's Survey of Professional Forecasters. We find that the loss function matters as exchange rate forecasters perform better under non-categorical loss functions, and the GDP forecasts have value up to two quarters ahead.","PeriodicalId":179699,"journal":{"name":"CESifo: Monetary Policy & International Finance (Topic)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124969432","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 analyse the extent to which firm-level uncertainty is affected by aggregate uncertainty. Firm-level uncertainty is constructed from a large and monthly panel dataset of manufacturing firms. We find that aggregate uncertainty has a positive and robust impact on firm-level uncertainty. This effect holds across different types of domestic and international measures of aggregate uncertainty. However, the size of the impact is heterogeneous and depends on certain firm characteristics and the state of the business cycle. For example, the widely used economic policy uncertainty index matters to all firms’ uncertainty only in recessionary periods, while it is relevant over the entire business cycle only to large firms’ uncertainty.
{"title":"The Impact of Aggregate Uncertainty on Firm-Level Uncertainty","authors":"J. Easaw, C. Grimme","doi":"10.2139/ssrn.3805460","DOIUrl":"https://doi.org/10.2139/ssrn.3805460","url":null,"abstract":"We analyse the extent to which firm-level uncertainty is affected by aggregate uncertainty. Firm-level uncertainty is constructed from a large and monthly panel dataset of manufacturing firms. We find that aggregate uncertainty has a positive and robust impact on firm-level uncertainty. This effect holds across different types of domestic and international measures of aggregate uncertainty. However, the size of the impact is heterogeneous and depends on certain firm characteristics and the state of the business cycle. For example, the widely used economic policy uncertainty index matters to all firms’ uncertainty only in recessionary periods, while it is relevant over the entire business cycle only to large firms’ uncertainty.","PeriodicalId":179699,"journal":{"name":"CESifo: Monetary Policy & International Finance (Topic)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129922575","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 studies how an increase in the number of armed groups operating within an area affects the amount of organized political violence. We use plausible exogenous variation in the number of armed groups in Pakistan, by exploiting the split of a major group due to the natural death of its leader. Employing difference-in-difference and instrumental variable regressions on geocoded incident and fatality data allows us to derive a causal effect: more groups lead to more political violence. By combining different data sources and implementing a new approach to deal with potential double-counting, we provide a proxy for counter-insurgency efforts by the government. We show that the increase in violence is primarily driven by the armed groups and not by responses of the government.
{"title":"Armed Groups in Conflict: Competition and Political Violence in Pakistan","authors":"M. Gassebner, Paul Schaudt, Melvin H. L. Wong","doi":"10.2139/ssrn.3633657","DOIUrl":"https://doi.org/10.2139/ssrn.3633657","url":null,"abstract":"This paper studies how an increase in the number of armed groups operating within an area affects the amount of organized political violence. We use plausible exogenous variation in the number of armed groups in Pakistan, by exploiting the split of a major group due to the natural death of its leader. Employing difference-in-difference and instrumental variable regressions on geocoded incident and fatality data allows us to derive a causal effect: more groups lead to more political violence. By combining different data sources and implementing a new approach to deal with potential double-counting, we provide a proxy for counter-insurgency efforts by the government. We show that the increase in violence is primarily driven by the armed groups and not by responses of the government.","PeriodicalId":179699,"journal":{"name":"CESifo: Monetary Policy & International Finance (Topic)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129565976","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}
Assessing the robustness of the results of econometric analysis is a long standing subject of lively research. The majority of the literature focuses on sensitivity to model specification, while the quantification of sensitivity to sets of influential observations has received relatively little attention. A major obstacle in this context is masking, a phenomenon where influential observations obscure each other, which makes their identification particularly challenging. We show how inferential measures are affected by influential sets of observations and present two adaptive algorithms aimed at identifying such sets. We demonstrate the merits of these algorithms via simulation studies and empirical applications. These exercises show that masking problems and a pronounced sensitivity to influential sets are present in a wide range of scenarios. Overall, our findings suggest that increased attention to influential sets is warranted and comprehensive robustness measures for regression analysis are required.
{"title":"Hidden in Plain Sight: Influential Sets in Linear Models","authors":"Nikolas Kuschnig, Gregor Zens, J. Cuaresma","doi":"10.2139/ssrn.3819102","DOIUrl":"https://doi.org/10.2139/ssrn.3819102","url":null,"abstract":"Assessing the robustness of the results of econometric analysis is a long standing subject of lively research. The majority of the literature focuses on sensitivity to model specification, while the quantification of sensitivity to sets of influential observations has received relatively little attention. A major obstacle in this context is masking, a phenomenon where influential observations obscure each other, which makes their identification particularly challenging. We show how inferential measures are affected by influential sets of observations and present two adaptive algorithms aimed at identifying such sets. We demonstrate the merits of these algorithms via simulation studies and empirical applications. These exercises show that masking problems and a pronounced sensitivity to influential sets are present in a wide range of scenarios. Overall, our findings suggest that increased attention to influential sets is warranted and comprehensive robustness measures for regression analysis are required.","PeriodicalId":179699,"journal":{"name":"CESifo: Monetary Policy & International Finance (Topic)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115111122","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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