Research articles for the 2019-03-10

Do Households Care About Cash? Exploring the Heterogeneous Effects of India's Demonetization
Karmakar, Sudipto,Narayanan, Abhinav
The recent demonetization exercise in India is a unique monetary experiment that made 86 percent of the total currency in circulation invalid. In a country where currency in circulation constitutes 12 percent of GDP, the policy turned out to be a purely exogenous macroeconomic shock that affected all agents of the economy. This paper documents the impact of this macroeconomic shock on one such systematically important agent of the economy: the household. By construction, the policy helped households with bank accounts in disposing of the demonetized cash. We use a new household-level data set to tease out the effects of this policy on households with no bank accounts relative to households with bank accounts. Our results show that the impact of demonetization on household income and expenditure has been transient with the major impact being seen in December-2016. We find that households with no bank accounts experienced a significant decrease in both income and expenditure in December-2016. There is significant heterogeneity in the impact across households in different asset classes. We also show evidence of recovery of household finances whereby households were able to smooth out consumption during the post demonetization period. However, this recovery phase is associated with an increase in household borrowing from different sources, primarily for the purpose of consumption. In particular, informal borrowing (money lenders, shops) increased substantially during this period. Thus, the policy although transient in nature, contributed to the unintended consequence of increased leverage for households.

Economic resilience from input-output susceptibility improves predictions of economic growth and recovery
Peter Klimek,Sebastian Poledna,Stefan Thurner

Modern macroeconomic theories were unable to foresee the last Great Recession and could neither predict its prolonged duration nor the recovery rate. They are based on supply-demand equilibria that do not exist during recessionary shocks. Here we focus on resilience as a nonequilibrium property of networked production systems and develop a linear response theory for input-output economics. By calibrating the framework to data from 56 industrial sectors in 43 countries between 2000 and 2014, we find that the susceptibility of individual industrial sectors to economic shocks varies greatly across countries, sectors, and time. We show that susceptibility-based predictions that take sector- and country-specific recovery into account, outperform--by far--standard econometric growth-models. Our results are analytically rigorous, empirically testable, and flexible enough to address policy-relevant scenarios. We illustrate the latter by estimating the impact of recently imposed tariffs on US imports (steel and aluminum) on specific sectors across European countries.

Elusive Longer-Run Impacts of Head Start: Replications Within and Across Cohorts
Remy J.-C. Pages,Dylan J. Lukes,Drew H. Bailey,Greg J. Duncan

Using an additional decade of CNLSY data, this study replicated and extended Deming's (2009) evaluation of Head Start's life-cycle skill formation impacts in three ways. Extending the measurement interval for Deming's adulthood outcomes, we found no statistically significant impacts on earnings and mixed evidence on other adult outcomes. Applying Deming's sibling comparison framework to more recent birth cohorts born to CNLSY mothers revealed mostly negative Head Start impacts. Combining all cohorts shows generally null impacts on school-age and early adulthood outcomes.

Evaluating Real Estate Mutual Fund Performance Using the Morningstar Upside/Downside Capture Rati
Kuhle, James L.,Lin, Eric C.
The purpose of this research is to explore the viability of utilizing the Morningstar upside/downside capture ratio (UDCR) as viable measure of mutual fund risk and its relation to return. This research examines and compares result of the Sharpe ratio to the Morningstar upside/downside capture ratio (UDCR) in an effort to determine if the UDCR might better explain the ex-post performance of the mutual funds examined. Three sectors of 268 mutual funds are examined; these include domestic equity real estate, domestic equity value funds, and global equity real estate as defined and reported on the Morningstar database. This research considers the traditional measures of risk which include the standard deviation of returns along with the Sharpe ratio. The empirical results suggest that UDCR may provide a more accurate fit in explaining real estate mutual fund returns than the Sharpe Ratio.

Individual Pension Risk Preference Elicitation and Collective Asset Allocation With Heterogeneity
Alserda, Gosse,Dellaert, Benedict G. C.,Swinkels, Laurens,van der Lecq, Fieke
Collectively organized pension plans must increasingly demonstrate that the risk preferences of their members are adequately reflected in the plans' asset allocations. However, whether funds should elicit individual members' risk preferences to achieve this goal, or whether they can rely on other indicators, such as socio-demographics, remains unclear. To address this question, we apply a tailored augmented lottery choice method to elicit individual pension income risk preferences from 7,894 members from five different pension plans. The results show that member risk preferences are strongly heterogeneous and can only partially be predicted from individual and plan characteristics. Differences in risk preference imply different optimal asset allocations. We find large welfare losses for heterogeneous members in pension plans with their current asset allocation because these allocations are safer than implied by members' preferences. We provide a framework for pension plans to gauge the need to elicit risk preferences among their members.

International Evidence on the Common Determinants of Volatility Persistence and Asymmetry
Chen, Shuning,Wang, Jian-Xin
This study presents empirical evidence that volatility persistence and asymmetry are jointly affected by market conditions captured by return and volatility. Using 28 equity market indices in developed and emerging countries, we show that daily volatility persistence increases with returns, especially negative returns, but decreases with volatility level. The dependence of volatility persistence on market conditions is termed the conditional volatility persistence. It has strong explanatory power for volatility variations, and often accounts for more volatility asymmetry than the classic leverage effect and volatility feedback. Daily volatility persistence is dominated by global market conditions in most developed markets, and by local market conditions in emerging markets.

Kernel Based Estimation of Spectral Risk Measures
Suparna Biswas,Rituparna Sen

Spectral risk measures (SRMs) belongs to the family of coherent risk measures. A natural estimator for the class of spectral risk measures (SRMs) has the form of $L$-statistics. In the literature, various authors have studied and derived the asymptotic properties of the estimator of SRM using the empirical distribution function. But no such estimator of SRM is studied considering distribution function estimator other than empirical cdf. We propose a kernel based estimator of SRM. We try to investigate the large sample properties of general $L$-statistics based on i.i.d cases and apply them to our kernel based estimator of SRM. We prove that the estimator is strongly consistent and the estimator is asymptotically normal. We compare the finite sample performance of the kernel based estimator with that of empirical estimator of SRM using Monte Carlo simulation, where appropriate choice of smoothing parameter and the user's coefficient of risk aversion plays an important role. Based on our simulation study we have estimated the exponential SRM of four future index-that is Nikkei 225, Dax, FTSE 100 and Hang Seng using our proposed kernel based estimator.

Modelling Utility Financial Viability Using Logistic Regression: Evidence From Florida
Acheampong, Daniel,Benford, Tanya,Volkan, Ara
Ratemaking is the mechanism that various state commissions use to establish utility rates for investorowned utilities. Using logistic regression, this study explains the need for a flexible model to determine the financial viability of such utilities. The study uses 47 Florida investor-owned water and wastewater utilities to assess financial viability from 2002 to 2013. The financial viability results obtained using the National Regulatory Research Institute (NRRI) model are compared to the results of a more rigorous logistics regression model developed in this study. First, the results show that the financial ratios currently used by the NRRI to determine the viability of utilities do not need to be all-inclusive. Second, using data from 2002 to 2013, the logistic regression model categorized the viability of these utilities into groupings different from those of the NRRI model. Third, the study shows that ratemaking is not a uniform process across all states and supports discontinuing usage of the NRRI standard viability model in favor of the logistic regression model that incorporates the same financial ratios used by the NRRI.

Monday Mornings: Individual Investor Trading on Days of the Week and Times Within a Day
Richards, Daniel W.,Willows, Gizelle
Individual investors’ demand for trading activity will vary over time according to their availability and desire to trade. Academic research has primarily investigated market wide trading activity, showing low trading activity on Mondays and high activity at the start and end of each day. It remains unknown whether individual investors’ trading behavior mimics these market patterns. Instead research on individual investors shows that they overtrade in general and are less likely to trade losses. We research trading activity for 7 200 UK investors, finding these investors actually prefer trading on Mondays and trade in a W-shaped intraday pattern. Further investigation revealed that investors increased their selling of losses on Monday mornings, suggesting investors utilise spare time to process difficult trading decisions.

Nowcasting Recessions using the SVM Machine Learning Algorithm
Alexander James,Yaser S. Abu-Mostafa,Xiao Qiao

We introduce a novel application of Support Vector Machines (SVM), an important Machine Learning algorithm, to determine the beginning and end of recessions in real time. Nowcasting, "forecasting" a condition about the present time because the full information about it is not available until later, is key for recessions, which are only determined months after the fact. We show that SVM has excellent predictive performance for this task, and we provide implementation details to facilitate its use in similar problems in economics and finance.

Privatizing Flood Insurance in the United States: Options, Challenges, and Pitfalls
Born, Patricia,Klein, Robert W.
In this paper, we examine the options, challenges, and potential pitfalls in expanding the role of the private sector in providing flood insurance in the United States. This topic that has garnered considerable interest given the problems facing the National Flood Insurance Program (NFIP). There are many advocates of "privatization" in some form as they see it as a way to ameliorate the problems afflicting the NFIP as well as providing benefits to consumers. The form of privatization that we give the most attention to involves legislative and regulatory measures that would make it easier for private companies to offer flood insurance on their own paper noting that there are other schemes that could be employed that would fall within the scope of privatization defined more broadly. While privatization has many advocates, it also has some detractors. We discuss both the potential benefits of the expansion of private flood insurance as it has been proposed as well as the principal concerns about certain provisions of the proposals that have been put on the table. Based on our analysis, it is our opinion that expanding the sale of private flood coverage, if done properly, would be welfare enhancing and in the public interest. The devil is in the details. This is where the rubber would meet the road in crafting a scheme that would yield the best possible outcomes for consumers while still making it attractive and feasible for carriers to substantially increase the provision of private flood insurance. Our objective is to provide insights into the relevant considerations and posit a scheme that would be workable and politically realistic.

Quantitative evaluation of consecutive resilience cycles in stock market performance: A systems-oriented approach
Junqing Tang,Hans R. Heinimann

Financial markets can be seen as complex systems that are constantly evolving and sensitive to external disturbance, such as systemic risks and economic instabilities. Analysis of resilient market performance, therefore, becomes useful for investors. From a systems perspective, this paper proposes a novel function-based resilience metric that considers the effect of two fault-tolerance thresholds: the Robustness Range (RR) and the Elasticity Threshold (ET). We examined the consecutive resilience cycles and their dynamics in the performance of two stock markets, NASDAQ and SSE. The proposed metric was also compared with three well-documented resilience models. The results showed that this new metric could satisfactorily quantify the time-varying resilience cycles in the multi-cycle volatile performance of stock markets while also being more feasible in comparative analysis. Furthermore, analysis of dynamics revealed that those consecutive resilience cycles in market performance were distributed non-linearly, following a power-law behavior in the upper tail. Finally, sensitivity tests demonstrated the large-value resilience cycles were relatively sensitive to changes in RR. In practice, RR could indicate investors' psychological capability to withstand downturns. It supports the observation that perception on the market's resilient responses may vary among investors. This study provides a new tool and valuable insight for researchers, practitioners, and investors when evaluating market performance.

ROSCAs As an Islamic Micro Finance Vehicle: The Concept, Key Drivers and Valuation
Al-Ajlouni, Ahmed
This article empirically investigates the drives for participation in Jamey'ah (literally, Society) in Egypt as a kind of Rotating Savings and Credit Associations (ROSCAs) that agree in its general framework with Islamic principles. The article also evaluates the sample’s experience with it in order to understand the influence of gender and income on the motives behind Society sharing and their valuation. The findings show that the amounts raised by societies are allocated to essential expenses. The tough procedures in case of borrowing; and low return in case of saving were the drivers behind leaving banks to finance via Societies as the results strongly suggest. The valuation of Societies indicate apparent impressive positive trend as the results strongly suggest. There is considerable empirical evidence showing that Societies can be a substitute to banks in providing personal loans.

Spreading the Fear: The Central Role of Cboe VIX in Global Stock Market Uncertainty
Smales, Lee A.
Construction of efficient portfolios is reliant on understanding the correlation between assets. If correlations change markedly during times of economic turmoil then investors are exposed to greater than desired risk levels at the most inopportune time. We examine the linkages between global stock markets using measures of market uncertainty (implied volatility). Using a sample of daily changes in G7 and BRIC implied volatility measures, over a 15-year sample period, we demonstrated that uncertainty in U.S. markets plays a pivotal role in global stock market uncertainty. “Fear is spread” across markets, as heightened uncertainty in U.S. markets is transmitted across global markets. Conversely, global markets do not appear to explain innovations in U.S. market uncertainty. We also report some evidence of market uncertainty linkages between European markets. Our results should provide some reassurance for investors in the sense that inter-dependencies do not appear to change in any meaningful way during the recession / crisis period of 2008-09.

Strategic Speed Choice by High-Frequency Traders under Speed Bumps
Aoyagi, Jun
We study how high-frequency traders (HFTs) strategically decide their speed level in a market with a random speed bump. If HFTs recognize the market impact of their speed decision, they perceive a wider bid-ask spread as an endogenous upward-sloping cost of being faster. We find that the speed elasticity of the bid-ask spread (slope of the endogenous cost function) negatively depends on the expected length of a speed bump since a longer delay makes market makers insensitive to HFTs' speed increment. Hence, speed bumps promote the investment of HFTs in high-speed technology by reducing the marginal cost of getting faster, undermining their intended purpose of protecting market makers. Depending on the expected length of a bump, an arms race among HFTs exhibits both complementarity and substitution. These findings explain the ambiguous empirical results regarding speed bumps and adverse selection for market makers.

Uncovering networks amongst stocks returns by studying nonlinear interactions in high frequency data of the Indian Stock Market using mutual information
Charu Sharma,Amber Habib

In this paper, we explore the detection of clusters of stocks that are in synergy in the Indian Stock Market and understand their behaviour in different circumstances. We have based our study on high frequency data for the year 2014. This was a year when general elections were held in India, keeping this in mind our data set was divided into 3 subsets, pre-election period: Jan-Feb 2014; election period: Mar-May 2014 and :post-election period: Jun-Dec 2014. On analysing the spectrum of the correlation matrix, quite a few deviations were observed from RMT indicating a correlation across all the stocks. We then used mutual information to capture the non-linearity of the data and compared our results with widely used correlation technique using minimum spanning tree method. With a larger value of power law exponent {\alpha}, corresponding to distribution of degrees in a network, the nonlinear method of mutual information succeeds in establishing effective network in comparison to the correlation method. Of the two prominent clusters detected by our analysis, one corresponds to the financial sector and another to the energy sector. The financial sector emerged as an isolated, standalone cluster, which remain unaffected even during the election periods.

Методически аспекти за прилагане на Ð"Ð"С върху финансовите услуги (Methodological Aspects of Applying VAT on Financial Services)
Angelov, Angel
Bulgarian Abstract: Ð"окладът обобщава предложените през последните няколко десетилетия политики за включването на финансовите услуги в облагаемата база на Ð"Ð"С. Ð'сяка една от тези политики (данъчни системи) се характеризира с множество приноси, но същевременно и с доста проблемни елементи. Изборът на конкретна политика трябва да е съобразен с региона, наличието/липсата на обща данъчна политика и разходите, необходими за налагането й.English Abstract: The report summarizes the policies proposed over the last few decades to include financial services in the taxable VAT base. Each of these policies (tax systems) is characterized by numerous contributions, but also with quite problematic elements. The choice of a specific policy must be in line with the region, the availability/lack of a common tax policy and the costs required to impose it.

Приватизация 30 лет спустя: масштабы и эффективность государственного сектора (Privatization 30 Years Later: Scope and Efficiency of the Public Sector)
Radygin, Alexander,Entov, Revold,Abramov, Alexander E.,Chernova, Maria,Malginov, Georgy
Russian Abstract: Авторы на основе краткого исторического экскурса анализируют современные приоритеты российской приватизации. Ð' докладе оцениваются размер государственного сектора экономики и целесообразность приватизации некоторых крупных российских компаний с государственным участием в условиях санкций. Показано, что сводные финансовые характеристики компаний с госучастием, как правило, хуже показателей частных компаний и зарубежных конкурентов, а совокупный доход по акциям первых меньше минимальной рыночной доходности по акциям. Эмпирическая часть доклада подготовлена по материалам выборки из 265 крупнейших частных и государственных российских компаний, по которым доступна публичная финансовая отчетность.English Abstract: The authors, on the basis of a brief historical excursion, analyze the current priorities of Russian privatization. The report assesses the size of the public sector and the feasibility of privatizing certain large Russian companies with state participation in the context of sanctions. It is shown that the consolidated financial characteristics of companies with state participation, as a rule, are worse than those of private companies and foreign competitors, and the total return on the shares of the former is less than the minimum market return on shares. The empirical part of the report is based on a sample of 265 largest private and state-owned Russian companies for which public financial reporting is available.