Using survey forecasts, we find that systematic errors in expectations of long-term inflation and short-term nominal earnings growth are the main driver of prices and return puzzles for bonds and stocks. We demonstrate this by deriving and testing a single necessary and sufficient condition based on accounting identities. Errors in expectations of short-term inflation and long-term nominal earnings growth do not play a role in either asset market. Because of these systematic errors, real cash flow expectations closely match aggregate bond and stock prices, leaving little room for time-varying discount rates. These expectations also accurately match key return puzzles for bonds and stocks: the rejection of the expectations hypothesis and stock return predictability. These results are consistent with a simple model in which agents believe the persistences of inflation and nominal earnings growth are magnified versions of the objective persistences.
{"title":"Real Cash Flow Expectations and Asset Prices","authors":"O R.Dela, S. Myers","doi":"10.2139/ssrn.3867773","DOIUrl":"https://doi.org/10.2139/ssrn.3867773","url":null,"abstract":"Using survey forecasts, we find that systematic errors in expectations of long-term inflation and short-term nominal earnings growth are the main driver of prices and return puzzles for bonds and stocks. We demonstrate this by deriving and testing a single necessary and sufficient condition based on accounting identities. Errors in expectations of short-term inflation and long-term nominal earnings growth do not play a role in either asset market. Because of these systematic errors, real cash flow expectations closely match aggregate bond and stock prices, leaving little room for time-varying discount rates. These expectations also accurately match key return puzzles for bonds and stocks: the rejection of the expectations hypothesis and stock return predictability. These results are consistent with a simple model in which agents believe the persistences of inflation and nominal earnings growth are magnified versions of the objective persistences.","PeriodicalId":332226,"journal":{"name":"USC Marshall School of Business Research Paper Series","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123758014","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 develop a political path dependence model that integrates the network embeddedness perspective and the literature on corporate political strategy to understand how firms adapt their political connections when anticorruption efforts lead to the turnover of government officials. We posit that although firms that have close associations with ousted corrupt officials can benefit from both removing existing political connections (“cleaning house”) and developing new connections with their successors (“hosting new guests”), political path dependence enables firms to do the former but constrains them from doing the latter. These effects are magnified when firms are highly dependent on the government, and when the ousted corrupt officials have great political power. Evidence from anticorruption campaigns in China between 2012 and 2018 lends support for our theoretical predictions.
{"title":"Cleaning House Before Hosting New Guests: A Political Path Dependence Model of Political Connection Adaptation in the Aftermath of Anticorruption Shocks","authors":"Han Jiang, Nan Jia, T. Bai, G. Bruton","doi":"10.1002/SMJ.3315","DOIUrl":"https://doi.org/10.1002/SMJ.3315","url":null,"abstract":"We develop a political path dependence model that integrates the network embeddedness perspective and the literature on corporate political strategy to understand how firms adapt their political connections when anticorruption efforts lead to the turnover of government officials. We posit that although firms that have close associations with ousted corrupt officials can benefit from both removing existing political connections (“cleaning house”) and developing new connections with their successors (“hosting new guests”), political path dependence enables firms to do the former but constrains them from doing the latter. These effects are magnified when firms are highly dependent on the government, and when the ousted corrupt officials have great political power. Evidence from anticorruption campaigns in China between 2012 and 2018 lends support for our theoretical predictions.","PeriodicalId":332226,"journal":{"name":"USC Marshall School of Business Research Paper Series","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128470329","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 provide a new explanation for the profitability anomaly along with a battery of supportive empirical tests. Our explanation is based on the observation that investors frequently value stocks by assigning similar price-to-earnings multiples to stocks with similar expected firm growth. This naive approach to valuation results in a positive relation between profitability and future stock returns, and the relation is stronger in firms with higher growth. The relation arises because less profitable firms must issue additional equity in the future to finance growth, thus diluting the claims of existing stockholders to future earnings and cash flows.
{"title":"Explaining the Profitability Anomaly","authors":"Ryan Erhard, Richard G. Sloan","doi":"10.2139/ssrn.3431482","DOIUrl":"https://doi.org/10.2139/ssrn.3431482","url":null,"abstract":"We provide a new explanation for the profitability anomaly along with a battery of supportive empirical tests. Our explanation is based on the observation that investors frequently value stocks by assigning similar price-to-earnings multiples to stocks with similar expected firm growth. This naive approach to valuation results in a positive relation between profitability and future stock returns, and the relation is stronger in firms with higher growth. The relation arises because less profitable firms must issue additional equity in the future to finance growth, thus diluting the claims of existing stockholders to future earnings and cash flows.","PeriodicalId":332226,"journal":{"name":"USC Marshall School of Business Research Paper Series","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132568916","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}
A. Daw, Antonio Castellanos, G. Yom-Tov, Jamol Pender, L. Gruendlinger
In customer support centers, a successful service interaction involves a dialogue between a customer and an agent. Both parties depend on one another for information and problem solving, and this interaction defines a co-produced service process. In this paper, we propose, develop, and compare new stochastic models for the co-production of service in a contact center. Using insights from service communication data, we model the service interactions using self-exciting and mutually exciting bivariate Hawkes processes, so that a correspondence from one party increases the likelihood of a response from the other party soon after. Moreover, our models incorporate both dynamic busyness factors that depend on the agent workload as well as dynamic factors that depend on the inner-mechanics of the interaction. To understand how well our Hawkes models describe the message-timestamps, we compare the goodness-of-fit of these models on contact center data from industry. We show that the word-count bivariate Hawkes model, which takes into account the mutual interaction and the amount of information provided by each party, fits the data the best. In addition to a great goodness-of-fit, the Hawkes models allow us to construct explicit expressions for the relationship between the correspondence rates of each party and the conversation progress. These formulae illustrate that the agent is more dominant in pacing the service along in the short term, but that the customer has a more profound effect on the duration of the conversation in the long run. Finally, we use our models to predict the future level of activity within a given conversation, through which we find that the bivariate Hawkes processes that incorporate the amount of information provided by each party or the sentiment expressed by the customer give us the most accurate predictions.
{"title":"The Co-Production of Service: Modeling Service Times in Contact Centers Using Hawkes Processes","authors":"A. Daw, Antonio Castellanos, G. Yom-Tov, Jamol Pender, L. Gruendlinger","doi":"10.2139/ssrn.3817130","DOIUrl":"https://doi.org/10.2139/ssrn.3817130","url":null,"abstract":"In customer support centers, a successful service interaction involves a dialogue between a customer and an agent. Both parties depend on one another for information and problem solving, and this interaction defines a co-produced service process. In this paper, we propose, develop, and compare new stochastic models for the co-production of service in a contact center. Using insights from service communication data, we model the service interactions using self-exciting and mutually exciting bivariate Hawkes processes, so that a correspondence from one party increases the likelihood of a response from the other party soon after. Moreover, our models incorporate both dynamic busyness factors that depend on the agent workload as well as dynamic factors that depend on the inner-mechanics of the interaction. To understand how well our Hawkes models describe the message-timestamps, we compare the goodness-of-fit of these models on contact center data from industry. We show that the word-count bivariate Hawkes model, which takes into account the mutual interaction and the amount of information provided by each party, fits the data the best. In addition to a great goodness-of-fit, the Hawkes models allow us to construct explicit expressions for the relationship between the correspondence rates of each party and the conversation progress. These formulae illustrate that the agent is more dominant in pacing the service along in the short term, but that the customer has a more profound effect on the duration of the conversation in the long run. Finally, we use our models to predict the future level of activity within a given conversation, through which we find that the bivariate Hawkes processes that incorporate the amount of information provided by each party or the sentiment expressed by the customer give us the most accurate predictions.","PeriodicalId":332226,"journal":{"name":"USC Marshall School of Business Research Paper Series","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124726665","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}
Firm Profitability - Does it really matter for shareholder return or ROE (return on equity)? Does this question sound oxymoron and antithetic? Not really. On the contrary, evidence has surfaced that Returns on equity - based on the shareholders' equity accounted in the balance sheet - is not really directly tied to firm's profitability because it is increasingly observed that more attention is given to short-term marginal gains of the stock rather than long-term value buildup for shareholders. And higher stock gains appear to be realized through trading on a short-term basis of frequent stock-buy & sell at the right time and speed. Notwithstanding what the conventional wisdom is, the disconnect between profitability and long-term ROE is becoming the hard truth in a modern stock market, while smart investors are achieving better returns through active trading.
{"title":"Does Profitability Really Matter? Marginality, Volatility & $ Trillion Question","authors":"Senthilkumar Muthusamy","doi":"10.2139/ssrn.3539940","DOIUrl":"https://doi.org/10.2139/ssrn.3539940","url":null,"abstract":"Firm Profitability - Does it really matter for shareholder return or ROE (return on equity)? Does this question sound oxymoron and antithetic? Not really. On the contrary, evidence has surfaced that Returns on equity - based on the shareholders' equity accounted in the balance sheet - is not really directly tied to firm's profitability because it is increasingly observed that more attention is given to short-term marginal gains of the stock rather than long-term value buildup for shareholders. And higher stock gains appear to be realized through trading on a short-term basis of frequent stock-buy & sell at the right time and speed. Notwithstanding what the conventional wisdom is, the disconnect between profitability and long-term ROE is becoming the hard truth in a modern stock market, while smart investors are achieving better returns through active trading.","PeriodicalId":332226,"journal":{"name":"USC Marshall School of Business Research Paper Series","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133278469","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 paper we study international linkages when forecasting unemployment rates in a sample of 24 OECD economies. We propose a Global Unemployment Factor (GUF) and test its predictive ability considering in-sample and out-of-sample exercises. Our main results indicate that the predictive ability of the GUF is heterogeneous across countries. In-sample results are statistically significant for Austria, Belgium, Czech Republic, Finland, France, Ireland, The Netherlands, Portugal, Slovenia, Sweden and United States. Robust statistically significant out-of-sample results are found for Belgium, Czech Republic, France, The Netherlands, Slovenia, Sweden and the United States. This means that the inclusion of the GUF adds valuable information to predict domestic unemployment rates, at least for these last seven countries.
{"title":"Forecasting Unemployment Rates with International Factors","authors":"Pablo M. Pincheira, Ana María Hernández","doi":"10.2139/ssrn.3510597","DOIUrl":"https://doi.org/10.2139/ssrn.3510597","url":null,"abstract":"In this paper we study international linkages when forecasting unemployment rates in a sample of 24 OECD economies. We propose a Global Unemployment Factor (GUF) and test its predictive ability considering in-sample and out-of-sample exercises. Our main results indicate that the predictive ability of the GUF is heterogeneous across countries. In-sample results are statistically significant for Austria, Belgium, Czech Republic, Finland, France, Ireland, The Netherlands, Portugal, Slovenia, Sweden and United States. Robust statistically significant out-of-sample results are found for Belgium, Czech Republic, France, The Netherlands, Slovenia, Sweden and the United States. This means that the inclusion of the GUF adds valuable information to predict domestic unemployment rates, at least for these last seven countries.","PeriodicalId":332226,"journal":{"name":"USC Marshall School of Business Research Paper Series","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134519567","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}
Is the supply of public liquidity important for alleviating financial crises? I quantify a general equilibrium model featuring the liquidity insurance channel: Banks demand public liquidity as insurance against liquidation losses during banking crises. Cheaper liquidity insurance increases banks' liquidity buffer, which increases bank lending and thus output. Supporting this channel, the calibrated model explains 42% of variations in the liquidity premium. Counterfactual analyses reveal that without QE1, the cumulative output will be lower by at least 1.4%. However, due to large existing liquidity supply, the recent QE infinity in response to the coronavirus is much less effective. Appendix can be found here: https://ssrn.com/abstract=3347232.
{"title":"Public Liquidity and Financial Crises","authors":"Wenhao Li","doi":"10.2139/ssrn.3175101","DOIUrl":"https://doi.org/10.2139/ssrn.3175101","url":null,"abstract":"Is the supply of public liquidity important for alleviating financial crises? I quantify a general equilibrium model featuring the liquidity insurance channel: Banks demand public liquidity as insurance against liquidation losses during banking crises. Cheaper liquidity insurance increases banks' liquidity buffer, which increases bank lending and thus output. Supporting this channel, the calibrated model explains 42% of variations in the liquidity premium. Counterfactual analyses reveal that without QE1, the cumulative output will be lower by at least 1.4%. However, due to large existing liquidity supply, the recent QE infinity in response to the coronavirus is much less effective. \u0000 \u0000Appendix can be found here: https://ssrn.com/abstract=3347232.","PeriodicalId":332226,"journal":{"name":"USC Marshall School of Business Research Paper Series","volume":"50 8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129809374","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}
Auditors’ fraud detection is critical – undetected frauds impose costs on users and auditors. We propose auditors’ fraud risk identification during end-of-audit analytical procedures is affected by working under a completion (“just get it done”) goal versus a “refuse to accept” goal (with a desired conclusion that fraud risks remain). In an experiment, a refuse to accept goal positively affects auditors’ belief task performance is important, prompting integrative processing, then a higher likelihood of identifying a fraud risk. While the refuse to accept goal increases this belief for low professional identity auditors, it does not lead to identifying the specific risk, only raising concerns with their superior. High identity auditors are more likely to identify the specific risk under the goal, but, consistent with experiencing a self-concept threat, do not show increased belief performance is important and are less inclined to raise concerns. Findings have implications for research and practice.
{"title":"Does a Completion Goal Impede Auditors’ Identification of Fraud Risk? The Benefit of a Refuse to Accept Goal and Influence of Professional Identity","authors":"T. Majors, Sarah E. Bonner","doi":"10.2139/ssrn.3502992","DOIUrl":"https://doi.org/10.2139/ssrn.3502992","url":null,"abstract":"Auditors’ fraud detection is critical – undetected frauds impose costs on users and auditors. We propose auditors’ fraud risk identification during end-of-audit analytical procedures is affected by working under a completion (“just get it done”) goal versus a “refuse to accept” goal (with a desired conclusion that fraud risks remain). In an experiment, a refuse to accept goal positively affects auditors’ belief task performance is important, prompting integrative processing, then a higher likelihood of identifying a fraud risk. While the refuse to accept goal increases this belief for low professional identity auditors, it does not lead to identifying the specific risk, only raising concerns with their superior. High identity auditors are more likely to identify the specific risk under the goal, but, consistent with experiencing a self-concept threat, do not show increased belief performance is important and are less inclined to raise concerns. Findings have implications for research and practice.","PeriodicalId":332226,"journal":{"name":"USC Marshall School of Business Research Paper Series","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129312639","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 study the geographical pattern of online word-of-mouth (WOM). Leveraging a unique research design (a 'quietly' launched WOM program), we measure online WOM of over 200,000 customers across the U.S. by tracking their WOM referrals on a national e-commerce platform. In parallel, we measure the offline environment of each customer (e.g. social environment such as neighbor interactions and mobility, and local environment such as demographics and retailer access) by combining a range of datasets from proprietary and public data sources (Facebook, Census, ESRI and SCCBS). While digital technologies have enabled customers to share at any location and to any destination, we find that the offline (social) environment of a customer still matters for the generation and movement of online WOM. First, a customer's offline social environment significantly explains online referral propensity, whereas local characteristics that are known to explain customer online behavior are not explanatory. Second, customer online referrals are either bounded locally (30% within the same zipcode) or point at destinations that are socially or demographically similar to the customer's local environment. Finally, there is a significant interaction between advertising channels and offline environment in creating WOM. Our findings on the geographical pattern of online WOM can guide firms' design of location-based interventions such as the allocation of advertising budget across geographical areas.
{"title":"Geographical Pattern of Online Word-of-Mouth: How Offline Environment Influences Online Sharing","authors":"Tianshu Sun, Y. Wei, Joseph M. Golden","doi":"10.2139/ssrn.3497493","DOIUrl":"https://doi.org/10.2139/ssrn.3497493","url":null,"abstract":"We study the geographical pattern of online word-of-mouth (WOM). Leveraging a unique research design (a 'quietly' launched WOM program), we measure online WOM of over 200,000 customers across the U.S. by tracking their WOM referrals on a national e-commerce platform. In parallel, we measure the offline environment of each customer (e.g. social environment such as neighbor interactions and mobility, and local environment such as demographics and retailer access) by combining a range of datasets from proprietary and public data sources (Facebook, Census, ESRI and SCCBS). While digital technologies have enabled customers to share at any location and to any destination, we find that the offline (social) environment of a customer still matters for the generation and movement of online WOM. First, a customer's offline social environment significantly explains online referral propensity, whereas local characteristics that are known to explain customer online behavior are not explanatory. Second, customer online referrals are either bounded locally (30% within the same zipcode) or point at destinations that are socially or demographically similar to the customer's local environment. Finally, there is a significant interaction between advertising channels and offline environment in creating WOM. Our findings on the geographical pattern of online WOM can guide firms' design of location-based interventions such as the allocation of advertising budget across geographical areas.","PeriodicalId":332226,"journal":{"name":"USC Marshall School of Business Research Paper Series","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130016472","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}
Felipe Aldunate, Dirk Jenter, Arthur Korteweg, Peter Koudijs
Does enhanced shareholder liability reduce bank failure? We compare the performance of around 4,200 state-regulated banks of similar size in neighboring U.S. states with different liability regimes during the Great Depression. The distress rate of limited liability banks was 29% higher than that of banks with enhanced liability. Results are robust to a diff-in-diff analysis incorporating nationally-regulated banks (which faced the same regulations everywhere) and are not driven by other differences in state regulations, Fed membership, local characteristics, or differential selection into state-regulated banks. Our results suggest that exposing shareholders to more downside risk can successfully reduce bank failure.
{"title":"Shareholder Liability and Bank Failure","authors":"Felipe Aldunate, Dirk Jenter, Arthur Korteweg, Peter Koudijs","doi":"10.2139/ssrn.3490815","DOIUrl":"https://doi.org/10.2139/ssrn.3490815","url":null,"abstract":"Does enhanced shareholder liability reduce bank failure? We compare the performance of around 4,200 state-regulated banks of similar size in neighboring U.S. states with different liability regimes during the Great Depression. The distress rate of limited liability banks was 29% higher than that of banks with enhanced liability. Results are robust to a diff-in-diff analysis incorporating nationally-regulated banks (which faced the same regulations everywhere) and are not driven by other differences in state regulations, Fed membership, local characteristics, or differential selection into state-regulated banks. Our results suggest that exposing shareholders to more downside risk can successfully reduce bank failure.","PeriodicalId":332226,"journal":{"name":"USC Marshall School of Business Research Paper Series","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129008090","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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