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Given the alleged uniqueness of Islamic stocks, it is expected that they should provide insurance when faced with adverse market conditions. This expectation is tested by assessing contagion, using 25 Islamic indexes during the period 2007–2017, by employing contemporary econometric techniques. The results reveal robust contagion effects of the financial crisis on Islamic stock indexes. Furthermore, we find Baker and Wurgler’s investor sentiment can predict Islamic stock returns during the crisis period. Our findings indicate that Islamic stocks cannot be used as a haven asset during financial turmoil.

Cultural dimensions have a significant impact on capital structure decisions, particularly in Islamic economies where unique personal, social and ethical values are closely integrated with culture. This study considers the relationship between four Hofstede cultural dimensions to explain their connection with the capital structure decisions of Shariah-compliant firms. Using a panel of 342 Shariah complaint companies from Malaysia, Saudi Arabia and Pakistan for the period 2013 to 2017, this study investigates the influence of cultural dimensions on short-term, long-term and total leverage in the presence of several firm- and country-specific variables. On average, Saudi Arabian firms witnessed comparatively higher percentages of all three debt classifications considered. Typically, determinants of debt do not otherwise differ significantly across the three countries. Firms also carefully consider asset structure and growth opportunities when raising debt capital. On the other hand, when tested alongside cultural dimensions, Islamic firms from countries with (a) higher power distance scores, (b) higher levels of individualism, (c) higher masculinity scores and (d) lower degrees of uncertainty avoidance exhibit a preference for long-term debt. This finding diverges from the existing literature on non-Islamic firms. Agency theory and pecking order theory predominate in explaining our findings.

Traditionally, equity mispricing has been documented as an important determinant of speed of adjustment to target leverage levels. More recently, the impact of Shari’ah compliance has been shown to significantly affect capital structure decisions. In this paper, we explore the effect of equity mispricing in Shari’ah compliant (vs. non-compliant) firms. We conduct our study on a comprehensive sample of Malaysian firms from year 1998–2016. We show that established findings in the dynamic trade-off theory do not hold for Shari’ah compliant firms. Shari’ah compliant firms increase their reliance on equity financing at greater levels than non-compliant firms when they are above target levels and equities are overpriced. In contrast, for Shari’ah compliant firms below target levels and where equity is under-priced, the rate of adjustment is slower than non-compliant firms. Our findings suggest that managers of Shari’ah compliant firms are inclined to time the equity market when above target levels to capture the impact of lower costs of equity during periods of over-valuation of equity. However, those managers tend to be reluctant to resort to debt financing when below target leverage even in the presence of equity under-pricing.

This paper analyses the effect of bank lending and fee income on Islamic and conventional bank's performance. The paper builds a theoretical model and provides empirical evidence to show that Islamic banks as compared to conventional banks can have a greater reliance on fee-based income than returns from loans to increase their profitability. Using data from a sample of 20 countries for the period from 2000 to 2015 for Islamic and conventional banks, we find that the bank fee is an important determinant of the profitability of an Islamic bank. Interestingly, many commonly used measures such as loan to deposit ratio do not affect the Islamic banks' profitability as much as they do for conventional banks. Our findings imply that Islamic banks' lower sensitivity to loan to deposit ratio may contribute to lower credit risk. However, an over-reliance on fee-based income may affect their growth, profitability and sustainability in the long run.

Over the last years, independent central banks were often criticized. Many critics felt that the fatal flaw of the current system lied in its independent nature. Some critics argued that the remedy to such problems was to replace independence with interdependence. Such a drastic measure is completely unnecessary. No more time should be lost discussing further the merits or the weaknesses of central bank independence. But taking central bank independence as a given, one should simply try to equip central bankers with the mandates, the tools, and the values best fitted to help them face future shocks. Deeper checks and balances with other institutions and the fair financing of investment by all economic agents, including startups and SMEs, are urgently necessary to head off financial crises that will inevitably arise in this era of growing wealth inequality, disruptive technologies and climate change.

This paper studies the asset pricing implications of industrial pollution. A long-short portfolio constructed from firms with high versus low toxic emission intensity within a given industry generates an average return of 4.42% per annum, which remains significant after controlling for risk factors. This pollution premium cannot be explained by several explanations, including existing systematic risks, investors' preference, market sentiment, political connections, and corporate governance. We propose and model a new systematic risk related to environmental policy uncertainty. We use the growth of environmental litigation penalties to measure regime change risk, and find that it helps price the cross-section of emission portfolios' returns.

Teacher performance scores inform education leaders’ management of teacher human resources. However, prior research has implied that different interpretations of performance criteria between teachers and their evaluators suppress teacher development. Although research has examined teacher perceptions of performance scores and compared teacher self-scores with researcher-generated scores, no work has estimated the statistical differences between self-scores and field-based evaluator scores. I applied structural equation modeling to a unique dataset of over 4,000 teacher self-scores and 4,000 evaluator scores of teacher performance to examine the extent to which teachers and evaluators applied a standards-based teaching performance rubric similarly. Consistent with prior work, some average self-scores exceeded average evaluator scores; however, evaluator-assigned scores exceeded self-scores on one indicator. The evidence also suggested that teachers and evaluators interpreted the meaning of two performance indicators differently. The findings imply that there are opportunities to strengthen evaluators’ and teachers’ shared understanding of teacher performance criteria. Teachers and evaluators might develop shared understandings by viewing videorecorded lessons and collaboratively interpreting teaching episodes using the performance criteria. Education leaders might also emphasize that preobservation conferences are an opportunity for evaluators and teachers to discuss performance criterion interpretations. As some selfscores exceeded evaluator scores, education leaders could introduce a consider-the-opposite scoring strategy, where evaluators consider two reasons that the score they want to give could be inaccurate, prompting stronger scoring justification, potentially leading to more accurate scoring.

We use longitudinal data from the income tax system to study the impacts of firms’ employment and wage-setting policies on the level and change in immigrant–native wage differences in Canada. We focus on immigrants who arrived in the early 2000s, distinguishing between those with and without a college degree from two broad groups of countries – the U.S., the U.K. and Northern Europe, and the rest of the world. Consistent with a growing literature based on the two-way fixed effects model of Abowd, Kramarz, and Margolis (1999), we find that firm-specific wage premiums explain a significant share of earnings inequality in Canada and contribute to the average earnings gap between immigrants and natives. In the decade after receiving permanent status, earnings of immigrants rise relative to those of natives. Compositional effects due to selective outmigration and changing participation play no role in this gain. About one-sixth is attributable to movements up the job ladder to employers that offer higher pay premiums for all groups, with particularly large gains for immigrants from the “rest of the world” countries.

We develop a model where persistent trade shocks create demand for a basket- backed stablecoin, such as Mark Carney's "synthetic hegemonic currency" or Facebook's recent proposal for Libra. In numerical simulations, we find four main results. First, because of general equilibrium effects of the basket currency on the volatility of currency values, overall demand for that currency is small. Second, despite scant holdings of the basket, its global reach may contribute to substantial increases in welfare if the basket is widely accepted, allowing it to complement holdings of sovereign currencies. Third, we calculate the welfare maximizing composition of the basket, finding that optimal weights depend on the pattern of international acceptance, but that basket composition does not significantly affect welfare. Fourth, despite potential welfare improvements, low demand for the basket currency from buyers limits sellers' incentives to invest in accepting it, suggesting that fears of a so-called global stablecoin replacing domestic sovereign currencies may be overstated.

The aim of the study was to investigate a perceived severity of religious intolerance, and reasons behind it, among different religious groups in Pakistan. A questionnaire measuring religious intolerance was completed by 199 university students (females M = 23.8 yrs, SD 5.3, and males M = 24.6 yrs, SD 5.6) from four religious groups: Sunni, Shia, Ahmadi, and Christian. Questions regarding the severity of intolerance were included as well as the following seven scales measuring possible causes for it: impact of the school curriculum, lack of knowledge about other groups, impact of hate literature, lack of social justice, family background and peer pressure, media impact, as well as external power influence and history. Respondents of all groups agreed upon the severe level of religious intolerance towards Ahmadis. Regarding the other religious groups, opinions differed. Sunni respondents rated the seven causes for religious intolerance as lower than the others. Sunni and Shia respondents rated the impact of the school curriculum as the significantly most important reason behind religious intolerance, whereas the Ahmadis and Christians rated hate literature as the most important reason. The results suggest that there is a need for further research into social factors that could reduce religious intolerance in Pakistan. Views of different religious groups need to be taken in consideration.

Efficient computational algorithms for bootstrapping linear regression models with clustered data are discussed. For ordinary least squares (OLS) regression, a new algorithm is provided for the pairs cluster bootstrap, along with two algorithms for the wild cluster bootstrap. One of these is a new way to express an existing method. For instrumental variables (IV) regression, an efficient algorithm is provided for the wild restricted efficient cluster (WREC) bootstrap. All computations are based on matrices and vectors that contain sums of squares and cross-products for the observations within each cluster, which have to be computed just once before the bootstrap loop begins. Monte Carlo experiments are used to study the finite-sample properties of bootstrap Wald tests for OLS regression and of WREC bootstrap tests for IV regression.

Problem definition: Online retailers disclose product availability to influence customer decisions as a form of pressure selling designed to compel customers to rush into a purchase. Can the revelation of this information drive sales and profitability? We study the effect of disclosing product availability on market outcomes—product sales and returns—and identify the contexts where this effect is most powerful. Academic/practical relevance: Increasing sell-out is key for online retailers to remain profitable in the presence of thin margins and complex operations. We provide insights into how their information-disclosure policy—something they can tailor at virtually no cost—can contribute to this important objective. Methodology: We collaborate with an online retailer to procure a year of transaction data on 190,696 products that span 1,290 brands and 472,980 customers. To causally identify our results, we use a generalized difference-in-differences design with matching that exploits one policy of the firm: it discloses product availability only for the last five units. Results: The disclosure of low product availability increases hourly sales—they grow by 13.6%—but these products are more likely to be returned—product return rates increase by 17.0%. Because returns are costly, we also study net sales—product hourly sales minus hourly returns—which increase by 12.5% after the retailer reveals low availability. Managerial implications: The positive effects on sales and profitability amplify over wide assortments and when low-availability signals are abundantly visible and disclosed for deeply discounted products whose sales season is about to end. In addition, we propose a data-driven policy that exploits these results by using machine learning to prescribe the timing of disclosure of scarcity signals in order to boost sales without spiking returns. History: This paper has been accepted as part of the 2019 Manufacturing & Service Operations Management Practice-Based Research Competition.

Using oil futures, we examine expectation formation and how it alters the macroeconomic transmission of shocks. Our empirical framework, where investors learn about the persistence of oil-price movements, successfully replicates the fluctuations in oil-price futures since the Late 1990s. By embedding this learning mechanism in an estimated model, we document that an increase in the persistence of TFP-driven fluctuations in oil demand largely accounts for investors' perceptions that oil-price movements became increasingly permanent during the 2000s. Learning alters the macroeconomic impact of shocks, making the responses time dependent and conditional on perceptions of shocks' likely persistence.

Problem definition: We study a practice-motivated multiperiod stochastic commodity procurement problem under price uncertainty with forward and spot purchase options. Existing approaches are based on parametric price models, which inevitably involve price model misspecification and generalization error. Academic/practical relevance: We propose a nonparametric, data-driven approach (DDA) that is consistent with the optimal procurement policy structure but without requiring the a priori specification and estimation of stochastic price processes. In addition to historical prices, DDA is able to leverage real-time feature data, such as economic indicators, in solving the problem. Methodology: This paper provides a framework for prescriptive analytics in dynamic commodity procurement, with optimal purchase policies learned directly from data as functions of features, via mixed integer linear programming (MILP) under cost minimization objectives. Hence, DDA focuses on optimal decisions rather than optimal predictions. Furthermore, we combine optimization with regularization from machine learning (ML) to extract decision-relevant data from noise. Results: Based on numerical experiments and empirical data, we show that there is a significant value of feature data for commodity procurement when procurement policy parameters are learned as functions of features. However, overfitting deteriorates the performance of data-driven solutions, which asks for ML extensions to improve out-of-sample generalization. Compared with an internal best-practice benchmark, DDA generates savings of on average 9.1 million euros per annum (4.33%) for 10 years of backtesting. Managerial implications: A practical benefit of DDA is that it yields simple but optimally structured decision rules that are easy to interpret and easy to operationalize. Furthermore, DDA is generalizable and applicable to many other procurement settings. History: This paper has been accepted as part of the 2019 Manufacturing & Service Operations Management Practice-Based Research Competition. Supplemental Material: The e-companion is available at https://doi.org/10.1287/msom.2020.0890 .

This study investigates the relevance of behavioural finance to decision making. Studies suggest that human decision making is not always rational. This paper examines three behavioural financial theories: expected utility, optimal expectation, and cumulative prospect theory, to test financial decision-making when facing skewed distribution in Vietnam. A survey was conducted using lottery tickets, with six questions divided into three pairs. Each pair was aligned with one set of theories, and the questions selected allowed conclusions to be drawn to explain participants' behaviour. The experiment tested 321 people from a variety of age ranges, genders and occupations. Findings show that gender and ages do not significantly impact the decision-making process. However, they explain the preference of participants who appear to be behaving irrationally but do show some rationality when facing the skewed distribution of return. Decision-makers look for all the possible probability payoffs and choose the best outcome with the low-frequency distribution. They follow optimal expectation and cumulative prospect theory ranking the increasing order payoff valued by the parameter and support the cumulative prospect theory set out by Tversky and Kahneman (1992) , showing "cognitive biases" and demonstrating that individuals routinely make decisions that contradict reasonable logic The behavioural finance theory is again proven to be crucial. It strongly complements the standard financial theory. Individuals show heuristic behaviour when decision making in random situations especially when facing skewed distribution.

This paper contends that the use of alternative constructs as Enterprise Risk Management (ERM) measures has made a partial contribution to the different and contradictory results provided by various empirical studies. It further argues that the comprehensive nature of Enterprise Risk Management implies that its adoption and implementation affect different aspects of firms and, therefore, the most appropriate construct to measure it should be equally comprehensive in order to capture all possible signals, outputs and effects from the features of a firm. Secondly, the specialised nature of banking operations and the associated risk necessitates risk measures that suit the peculiarities of the sector and in this study we have proposed banking sector specific ERM model. In this regard, we propose a comprehensive methodology and multifaceted approach to determining ERM measures for the banking sector, taking cognisance of the various components of ERM and the specific needs of the sector. In our proposed comprehensive methodology for determining ERM measures for the banking sector, we combined two important models: the ERM model for the banking sector and the CAMELS model for assessing the performance of banks. The integration of these two models provides a comprehensive and all-encompassing approach for determining ERM measures for the banking sector. Our model is novel and offers a significant contribution to the literature of bank risk management. Our model provides a comprehensive risk management framework for bank executives, bank risk managers, the board members of banks, central banks and the authorities responsible for financial sector stability.

This study aims to evaluate the volatility structure of equity returns in an emerging market. We test the persistence and asymmetries in the volatility structure of equity returns in the Pakistan stock exchange (PSX) between 2006 and 2020. The volatility dynamics are assessed using multiple symmetric and asymmetric variants of GARCH family models. We also introduce News Impact Curves to analyze the presence of asymmetries in the volatility of the returns. Our results demonstrate that the volatility is persistent only in daily returns but not in weekly and monthly returns. Similarly, asymmetries were observed for daily returns implying that news arriving in the market continuously does impact investors' sentiment and behavior. However, this phenomenon subdues when the period is extended, reflecting that PSX is efficient in semi-strong form. These findings have important implications for asset management, instrument pricing, cost of capital estimations, and portfolio optimization.

The role of debt in capital structure and firms' performance has a great novelty in reducing market imperfections that improve firms' value. This study integrated the qualitative and quantitative aspects of capital structure and firms' performance in 56 stock exchange-listed companies of Jordan by using the time series data from 2012 to 2016. The results confirmed the "stewardship theory," "pecking order theory," and "concentrated ownership theory," while contractionary monetary instruments diffuse the recessionary phase in a country. The results confirmed a U-shaped relationship between debt and Tobin's Q in mediation with the country's per capita income. In contrast, an inverted U-shaped relationship found between market capitalization and a firm's performance in intervention with domestic credit provided by the financial sector (DCPFS). These results are essential in the light of CG theories to stabilize the firm's internal and external issues, which are further optimized by government financial agencies to energize macroeconomic policies for sustained growth.

Our study investigates the impact of US foreign investments on total factor productivity (TFP) growth, controlling for the innovation capability of host countries, for a large dataset of 61countries from 1988 to 2017. Using the panel system GMM approach, our study presents some interesting findings. First, we reveal that foreign direct investment (FDI) has a negative effect on the productivity growth of all host countries. This finding suggests that FDI does not necessarily enhance the productivity growth of host countries. We also use R&D expenditures of multinational companies (MNEs) as an alternative for FDI to filter out any supplementary effects in technology transfer. The results indicate a negative R&D effect on the productivity growth of OECD countries and a positive effect on developing countries. We also find that the technology gap, when measured as labor productivity, only enhances the TFP growth of OECD countries, but when it is measured as innovation capability, the technology gap is found to decrease TFP growth in developing countries. These findings contrast against the theoretical assumption that a large technology gap (relative backwardness) increases the TFP growth of host countries.

In the context of the debate on Exchange Rate Pass-Through (ERPT) under inflation targeting regimes, this study analysis the ERPT in inflation targeting and non-targeting economies of ASEAN-5. Employing a Non-linear Autoregressive Distributed Lag (N-ARDL) framework on data from 2000: Q1 to 2019 Q:4, our key empirical findings suggest that the exchange rate shocks do lead to significant changes in inflation. There is also prima facie evidence of asymmetric effects of exchange rate shocks in Singapore, Philippines, and Indonesia and the results varied between and among inflation targeting and non-targeting countries. The results also varied in the short and long-terms, whereas in the long-run, asymmetric effects of real exchange rate persist only for Indonesia and Singapore. Regardless of the inflation targeting or non-targeting regime, oil price shocks are found to be the most crucial factor with the largest impact on inflation in ASEAN-5 economies. Money supply and output growth also found to have some effect on inflation, though the results varied among countries. Our findings have profound implication for monetary policy formulation and price stability.

In this paper we test two recently developed liquidity measures the Return-to-Turnover (hereafter RtoTR) proposed by Florackis et al. (2011) and Return-to-Volume (hereafter RtoV) recommended by Amihud, 2002 , for 386 companies listed on the Pakistani Stock Exchange (PSX). Our data is obtained from January 2005 to December 2019. We firstly show the Amihud, 2002 ratio has limited ability to distinguish illiquidity from size effects in asset pricing. Second, the Florackis et al. (2011) measure has distinct features to overcome the limitations of the Amihud, 2002 ratio in the PSX. Our results show that the Capital Asset Pricing Model cannot completely account for the significant RtoV premium. However, this weak evidence for the existence of this premium disappears when Fama–French or Carhart alphas are considered as measures of risk-adjusted performance. This suggests that the RtoTR price impact ratio is more effective in the PSX compared to the RtoV ratio. Our findings suggest that both trading frequency and trading cost are significant factors in examining the returns. The RtoV ratio has a negative correlation with the market capitalization, which suggests that small stocks are inherently illiquid.

This study examines the impact of house price on money demand in case of China for the period of 1988Q1-2017Q4. The present study used different estimators, which are robust to handling the endogeneity issues in the data, to capture the long-run effect of housing price index on money demand while controlling for interest rate, gross domestic product and consumer price index. The results suggest that house prices along with GDP, inflation and interest rate are important factors in explaining the money demand in China. To capture the vulnerability periods and identify the behaviour of the money demand and house price index variables in China, this study employs wavelet power spectrum. The results further show that there was a significant vulnerability in money demand between 2006 and 2012 in the short and medium terms. Besides, in order to identify the co-movement between house price and money demand in China, the continuous wavelet coherence approach is applied. The outcomes of continuous wavelet coherence approach reveal that there is strong linkage between money demand and house price index between 2002 and 2018 at both short and long terms. The results show that there is a positive and significant correlation between money demand and house price index in China. Thus, house price index can be a predictive factor for future money demand at low, middle and high frequencies.

We investigate the impact of asymmetric information on the investment decisions of firms and analyze the effect of asymmetric information on the over-investment and under-investment of firms. Further, we examine the effect of leverage on the investment behavior of firms and check this association in the presence of asymmetric information. We extract data from DataStream of 280 non-financial firms listed at Pakistan Stock Exchange over the period of 2000 to 2018. We apply the Fixed Effect Model to analyze the data and System Generalized Method of Moments to check the robustness of the results. We find that asymmetric information negatively affects the investment decisions of firms. Due to asymmetric information investment decreases rapidly as compared to increase in investment. Further, leverage is an important determinant of investment decisions and the presence of asymmetric information increases the adverse effect of leverage on the investment of firms.

This study spotlights the determinants of Chinese outward foreign direct investment in Pakistan under the China Pakistan Economic Corridor using time series data. The stationarity was checked through augmented dicky fuller tests, and an auto-regressive distributive lag bounds test confirm long-run association among exchange rate, inflation, corruption, law & order situation, and Chinese outward foreign direct investment. The study conducted auto-regressive distributive lag (ARDL) for the short-run and long-run equilibrium covering annual time series data from 1990 to 2017. The empirical results indicate that exchange rates, inflation, and corruption have a negative and statistically significant effect on China's outward foreign direct investment in the host country. In contrast, law and order situations have an insignificant association with outward foreign direct investment. The findings further demonstrate that the error correction term is negative and highly significant at a 1 % level of significance. This is another indication of a stable long-run association among the variables. The estimated error correction term coefficient is −0.102, recommends that the short-run disequilibrium can be corrected at the speed of 10 %. Moreover, in the short run, corruption, inflation, and law and order are significantly affecting outward foreign direct investment. At the same time, export has no significant impact on outward foreign direct investment in the short run.

© 2020 Board of Trustees of the University of Illinois This study examines whether the capital requirements under Basel III are effective in enhancing the profitability and efficiency of the banking sector. Drawing on a sample of the largest commercial banks from the UK and Australia over the period from 2000 to 2019, we employ the FMOLS (Fully Modified OLS) and DOLS (Dynamics OLS) estimation approaches. The results indicate that stricter capital ratio increases operating earnings, whist it fails to improve bank profitability and bank efficiency. Our findings cast doubts on the effectiveness of tax policy in the observed banks. Further empirical testing shows an optimal capital structure in which the banks can achieve the best performance. Interestingly, these optimal ratios are broadly in line with the minimum common equity ratio required under Basel-III. The macroeconomic outlook also contributes to the performance of British and Australian banks. British banks are found to perform well under inflationary pressure and higher policy rates, contrary to the Australian banks whose performance deteriorates. Our results hold across different samples, efficiency, and profitability measures and various estimation models.

This brief paper sets out an underappreciated practically oriented paradox and its methodological implications. The paradox is highly relevant to central banks and any organization or agent that seeks to match or anticipate central bank policy, such as other actors in banking and finance. Specifically, there is a divergence between the statistical requirement of stationarity and any macroeconomic policy objective that involves a target that takes a consistent and positive value. This is not merely an esoteric issue of interest to statisticians. It has fundamental implications for policy contexts. When achieved, any policy target, such as inflation targeting, will necessarily result in a unit root. As such, an unintended consequence of successful policy is non-stationarity, which means policy is permanently seeking to actualise conditions that are at cross-purposes with typical analytical statistical requirements. The point and its significance are illustrated beginning with a simple AR model and artificial inflation dataset.

Several interdisciplinary studies based on 2007–2008 global financial crisis to measure the causes of crisis, for e.g. firm value, stock market efficiency, corporate governance and macroeconomic performance, and relate all sources of crisis to prior studies. This paper examined the post financial crisis impact the short-term market responses of Hong Kong domestic acquisitions by separating target companies into two samples: Hong Kong targets and Mainland China targets from period of 2012–2016. We have used asset pricing models to estimate the market reaction to the acquisition announcement. We have also analysed the impact of several bid and firm characteristics on bidders’ short-term operating performances. Our findings suggest that: (i) acquisition events in both target markets, bidders earn significant positive abnormal returns but market responses of Mainland China target acquirers are much better. There is an inverse relationship between bidders’ post-acquisition abnormal returns and the level of competition in their targets’ market; (ii) companies bidding for Hong Kong targets obtain higher abnormal returns with cash-financing acquisitions, large relative size targets, single acquisitions, related acquisitions, small market value, more free cash flows, low leverage and high profitability; (iii) firms acquiring Mainland China targets benefit more from stock payment takeover events, large relative size target, multiple acquisitions, related acquisitions, large market value, less free cash flows, high leverage and high profitability.

Despite the well-documented mixed results of hedging on firm value, empirical evidence of why hedging reduces firm value is rare. Theory suggests that hedging can increase firm value by reducing bankruptcy cost and volatility, although it can also decrease firm value through a manager’s utility maximization. This study explores the reduction of market dependence and the over-investment hypothesis that results in decreasing firm value. By studying UK domiciled oil and gas companies, we found that capital expenditure accompanied by hedging reduces firm value, although capital expenditure itself increases firm value. This effect is pronounced when capital expenditure is made by firms with foreign operations, suggesting that hedging reduces the effect of the market’s monitoring role and, therefore, capital expenditure with hedging tends to be perceived as over-investment. This paper is one of the first studies that empirically examine the reduction of market dependence and over-investment through hedging.

Highlights • Directional spillover effects and connectedness for both return and volatility. • Nine US dollar exchange rates of globally most traded currencies. • Asymmetric spillovers and connectedness among these currencies with trade policy uncertainty. • The stronger volatility spillover than the return connectedness. • The role for predicting currency market dynamics with the trade policy uncertainty patterns., This paper analyses the directional spillover effects and connectedness for both return and volatility of nine US dollar exchange rates of globally most traded currencies under the influence of trade policy uncertainty. We find two interesting results over the study period ranging from December 1993 to July 2019. First, there exists asymmetric spillovers and connectedness among the considered exchange rates when trade policy uncertainty is present. Second, the volatility spillover is stronger than the return connectedness between exchange rate and trade policy uncertainty. These findings are robust to the presence of economic policy uncertainty effects. Concomitantly, the trade policy uncertainty patterns are also found to be useful for predicting currency market dynamics. Our findings contribute to the debate on the impact of trade policy uncertainty on the global economy and financial sector.

This study measures financial inclusion for developing countries. Given that financial inclusion is determined by three dimensions: penetration, availability, and use of financial services, this study develops a composite financial inclusion index (FI index) by adding “mobile money”–related indicators to the three dimensions to correspond to the degree of financial inclusion in these economies. To address the main research question, a measure of financial inclusion is constructed using a two-stage principal component analysis (PCA) method by assigning weights endogenously. Data were collected through secondary sources, including the World Bank (WB) and International Monetary Fund (IMF) reports for 2012–2018International Monetary Fund, 2020 International Monetary Fund (IMF) reports for 2012–2018. A new detailed index of financial inclusion measurement termed overall FI index was built based on the study. It is a useful tool for policymaking and evaluation. Our composite FI index is easy to calculate and comparable across economies over time. Particularly, this approach can address the criticism of arbitrary weight selection and comprehensively reflects the degree of financial inclusion.

The insurance industry in the Muslims countries has been making faster growth during the last few decades. The main objective of this paper is to examine the relationship of insurance sector with income per capita in Muslim countries. The countries selected for this analysis are 41 and the time span covered is from 1995 to 2019. The selection of cross-sections and time span is dictated by the availability of data. A number of estimators are used to rigorously analyze the hypothesized relationship, including a couple of the most contemporary macro-panel estimators such as pooled mean group (PMG), common correlated effects mean group (CCEMG), and augmented mean group (AMG). Neutral effect is found for life and non-life insurance penetration on income per capita, which can be attributed to beliefs in Muslim countries. However, we found positive long-run relationship between total insurance activity and income per capita, which can be due to complementarity between life and nonlife insurance activity. The results are found robust after applying robustness checks.

This study examines the impact of bonded zone policy on the performance of firms. We use a difference-in-differences approach and exploit differences in the timing of bonded zone approval as our id...

This paper investigates the relationship between structural change and regional economic growth in Indonesia. We utilize several measures of structural change, i.e. structural change index, norm absolute value index, shift-share method, and effective structural change index, for 30 provinces over the period 2005-2018. We show that the structural change has occurred across provinces, even though it is slowing, towards an agricultural-services transition. By employing dynamic panel data models, this study shows that structural change is a significant determinant of growth. However, structural change matters for growth only if there is an increase in productivity, not only a movement of labor across sectors. An improvement in productivity within sectors and a movement of labors to other sectors with better productivity lead to a better economic development.

This article addresses the challenge of combining ecosystem protection with economic development. The setting is societies living near a national park in a poor and peripheral part of Indonesia. Da...

This paper explores the microfoundations of consumption models and quantifies the macro implications of consumption heterogeneity. We propose a new empirical method to estimate the response of consumption to permanent and transitory income shocks for different groups of households. We then apply this method to administrative data from Denmark. The large sample size, along with detailed household balance sheet information, allows us to finely divide the population along relevant dimensions. We find that households that stand to lose from an interest rate hike are significantly more responsive to income shocks than those that stand to gain. Following a 1-percentage-point interest rate increase, we estimate that consumption growth decreases by a 1/4 percentage point through this interest rate exposure channel alone, making this channel substantially larger than the intertemporal substitution channel that is at the core of representative agent New Keynesian models.

The Belt and Road (B&R) is a major initiative and vision for China and the world to jointly create prosperity. Based on the data of resident credit card consumption in 291 cities in China from 2011 to 2016, this article establishes a consumption relationship model for cities along the B&R to investigate the impact of the initiative on resident consumption. Through the DID model, there are the following findings. First, the B&R Initiative has a significant positive impact on the resident consumption in cities along the route. Second, the B&R Initiative has a significant effect on the promotion of various industries, and the crowding-out effect of government investment is relatively small. The research conclusions are of reference significance for policy formulation on the specific practice path and detailed measures of the B&R Initiative.

This paper furthers and updates the research on the nature of the so-called global trade slowdown. Not only do we explain and discuss the determinants of this phenomenon, but we also offer an empirical description of the recent evolution of trade and trade elasticity. With the purpose of testing whether this is a structural phenomenon or not, we build an Error Correction Model for both world and regional data on trade and income using data from the World Bank for the period 1970-2017. World, OECD and Asian countries trade elasticity figures show a remarkable reduction after the hyperglobalization period (1986-2001), opposed to those of Latin America where trade volume has not stagnated so much. This slowdown might have major consequences for any country, but especially for those which have relied more intensively on trade as an engine for growth.Keywords: Global trade, Trade-income elasticity, ECM. JEL: C22, F15.

We introduce a cross-entropy (CE) indicator to quantify the extent to which two input-output tables or two tables with results based on input-output analysis differ from each other. Our work deploys a unique feature of the CE indicator: it can be decomposed, allowing for matrix comparisons at various levels within one coherent framework. To illustrate the power of this approach, we apply the technique to five multi-region input-output (MRIO) tables for 2011, derived from the Eora, EXIOBASE, GTAP, OECD and WIOD databases. We make pairwise comparisons between MRIOs and between global value chain (GVC) computations based on these MRIOs. We find that answers to questions related to broader aggregates are generally quite similar, but that answers to questions at the level of single industries can be rather different across MRIOs.

The ‘M4’ forecasting competition results were featured recently in a special issue of the International Journal of Forecasting and included projections for demographic time series. We sought to investigate whether the best M4 methods could improve the accuracy of small area population forecasts, which generally suffer from much higher forecast errors than regions with larger populations. The aim of this study was to apply the top ten M4 forecasting methods to produce 5- and 10-year forecasts of small area total populations using historical datasets from Australia and New Zealand. Forecasts were compared against the actual population numbers and forecasts from two simple benchmark models. The M4 methods were found to perform relatively well compared to our benchmarks. In the light of these findings, we discuss possible future directions for small area population forecasting research.

Can tax regimes shape the incentives of governments to engage in armed conflict? India’s Maoist belt contains a large share of the country’s most valuable mineral deposits. Indian mining royalties benefit the States, but they are set by the central government. States are largely responsible for counter-insurgency operations within their territory. Therefore, the royalty regime could shape the incentive of states to support counter-insurgency efforts. This paper exploits the introduction of a 10% ad valorem tax on iron ore that was responsible for a 10-fold increase in royalty collections by the affected State governments. In a panel of district-level violence outcomes between 2007 and 2013, we find that the royalty hike was followed by a significant intensification of violence in districts with iron ore deposits compared to other areas. We also show that the higher royalty rates are followed by an increase in illegal mining activity, suggesting that the control of mineral resources underpins the observed intensification in violence.

This paper analyzes Okun’s Law for Spain using regional data. The results confirm a very high Okun coefficient for Spain, with a high degree of regional heterogeneity. Furthermore, we find that panel data techniques provide notably more stable estimates than time series techniques applied to the same regional data. Finally, the results reveal a remarkable degree of regional heterogeneity in cyclical asymmetry in Okun’s Law for the Spanish case. Keywords: Unemployment; Okun’s Law; Economic Cycles; Regional Growth. JEL: E24, E32, R11.

When vacancies are filled, the ads that were posted are often not withdrawn, creating "phantom" vacancies. The existence of phantoms implies that older job listings are less likely to represent true vacancies than are younger ones. We assume that job seekers direct their search based on the listing age and so equalize the expected benefit of a job application across listing age. Forming a match with a vacancy of age α creates a phantom of age α with probability β and this leads to a negative informational externality that affects all vacancies of age α and older. Thus, the magnitude of this externality decreases with the age of the listing when the match is formed. Relative to the constrained efficient search behavior, the directed search of job seekers leads them to over-apply to younger listings. We illustrate the model using US labor market data. The contribution of phantoms to overall frictions is large, but, conditional on the existence of phantoms, the social planner cannot improve much on the directed search allocation.

In this research, canola meal was densified using bio-additives including alkali lignin, glycerol, and l -proline. The fuel pellet's formulation was optimized. The best fuel pellet demonstrated relaxed density and mechanical durability of 1015 kg/m3 and 99.0%, respectively. Synchrotron-based computer tomography technique indicated that lack of water in pellet formulation resulted in a twofold increase in pellet porosity. Thermogravimetric analysis showed that ignition temperature (240 °C) and burn-out temperature (640 °C) for fuel pellet were smaller than those for coal. Impacts of process parameters were evaluated on the quality of the gas product obtained from pellet's steam gasification and hydrothermal gasification. The gasification experiments showed production of untreated syngas with a suitable range of H2/CO molar ratio (1.3–1.6) using steam gasification. Hydro-thermal gasification produced a larger molar ratio of H2/CO (1.8–51.2) for the gas product. Modeling of pellet's steam gasification showed an excellent agreement with experimental results of steam gasification.

The crisis of 2007-08 called for a renewal of banking regulation that took the shape of a shift toward macroprudential policy. However, a comprehensive assessment of the current state of financial regulation reveals that this shift is incomplete. In particular, the notion of risk that lies at the heart of the Basel framework is still blind to extreme events. Climate risk and pandemic risk fall into this category. The purpose of this article is twofold. On the one hand, we point out why current banking regulation is not adequate to face risks whose origin is grounded outside financial markets – as is the case for both the pandemic and the climate risks –; on the other hand, we offer avenues for reforming macroprudential regulation in a way that would allow to take those risks into account.

Structural VAR models are routinely estimated by Bayesian methods. Several recent studies have voiced concerns about the common use of posterior median (or mean) response functions in applied VAR analysis. In this paper, we show that these response functions can be misleading because in empirically relevant settings there need not exist a posterior draw for the impulse response function that matches the posterior median or mean response function, even as the number of posterior draws approaches infinity. As a result, the use of these summary statistics may distort the shape of the impulse response function which is of foremost interest in applied work. The same concern applies to error bands based on the upper and lower quantiles of the marginal posterior distributions of the impulse responses. In addition, these error bands fail to capture the full uncertainty about the estimates of the structural impulse responses. In response to these concerns, we propose new estimators of impulse response functions under quadratic loss, under absolute loss and under Dirac delta loss that are consistent with Bayesian statistical decision theory, that are optimal in the relevant sense, that respect the dynamics of the impulse response functions and that are easy to implement. We also propose joint credible sets for these estimators derived under the same loss function. Our analysis covers a much wider range of structural VAR models than previous proposals in the literature including models that combine short-run and long-run exclusion restrictions and models that combine zero restrictions, sign restrictions and narrative restrictions.

Online matching platforms require new approaches to market design because firms can now control many aspects of the search and interaction process through various IT-enabled features. Although choice capacity—the number of candidates a user can view and select—is a key design feature of online matching platforms, its effect on engagement and matching outcomes remains unclear. We examine the effect of different choice capacities on market performance by conducting a randomized field experiment in collaboration with an online dating platform. Specifically, we design four treatment groups with different choice capacities in which users can only interact with other users in the same group and randomly assign the users to the treatment groups. We find that providing more choice capacity to male and female users has different effects on choice behaviors and matching outcomes. Although increasing the choice capacity of male users yields the highest engagement, increasing the choice capacity of female users is the most effective method to increase matching outcomes. We empirically demonstrate four mechanisms underlying the effectiveness of different choice capacity designs and generalize our findings by discussing how choice capacity can be designed to increase engagement and matching outcomes.

The output gap, the difference between potential and actual output, has a direct impact on policy decisions, e.g., monetary policy. Estimating this gap and its further analysis remain the subject of controversial debates due to methodological problems. We propose a local polynomial regression combined with a Self-Exciting Threshold AutoRegressive (SETAR) model and its forecasting extension for a systematic output gap estimation. Furthermore, local polynomial regression is proposed for the (multivariate) OECD production function approach and its reliability is demonstrated in forecasting output growth. A comparison of the proposed gap to the Hodrick–Prescott filter as well as to estimations by experts from the FED and OECD shows a higher correlation of our output gap with those from those economic institutions. Furthermore, sometimes gaps with different magnitude and different positions above or below the trend are observed between different methods. This may cause competing policy implications which can be improved with our results.

This paper exploits a large-scale auction experiment conducted by two Chinese government treasury security issuers—the Chinese Development Bank and the Export-Import Bank—to investigate whether treasury securities should be sold through uniform price or discriminatory price auction mechanisms. Based on the outcomes of more than 300 treasury securities issued through an alternating auction-rule market experiment, we find that yield rates of the two auction formats are not statistically different. Further, these estimates indicate there is no significant economic difference in terms of revenue between the two auction mechanisms. This result is robust across different bond yield-rate measurements and participation behavior. (JEL D44, E63, G12, O16, P34)

While economic theories indicate that market power by downstream firms can potentially counteract market power upstream, antitrust policy is opaque as to whether to incorporate countervailing market power in merger analyses. We use detailed national claims data from the health care sector to evaluate whether countervailing insurer power does indeed limit hospitals' exercise of market power. We estimate willingness-to-pay models to evaluate hospital market power across analysis areas. We find that countervailing market power is important: a typical hospital merger would raise hospital prices 4.3% at the 25th percentile of insurer concentration but only 0.97% at the 75th percentile of insurer concentration.

Following state-level legal changes that increase labor dismissal costs, firms increase their innovation in new processes that facilitate the adoption of cost-saving production methods, especially in industries with a large share of labor costs in total costs. Firms with high innovation ability exhibit larger increases in process innovation and capital-labor ratios - an effect driven by both increases in capital investment and decreases in employment. By facilitating the adjustment of the input mix when conditions in input markets change, innovation ability allows firms to mitigate value losses and is a key driver of their performance.