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We study systemic risk in a supply chain network where firms are connected through purchase orders. Firms can be hit by cost or demand shocks, possibly leading to defaults. These shocks propagate through the supply chain network via input-output linkages between buyers and suppliers. Firms endogenously take contingency plans to mitigate the impact generated from disruptions. They reroute undelivered orders to alternative buyers and switch excess demand to different suppliers. We show that, as long as firms have large initial equity buffers, network fragility is low if both buyer and supplier diversification is low. We argue that horizontal mergers may lead to a more fragile network if firms have small initial equity buffers. We find that a single sourcing strategy is beneficial for a firm only if the default probability of the firm's supplier is low. Otherwise, a multiple sourcing strategy is ex-post more cost effective for a firm.

We examine how firms adjusted their open innovation strategy in response to the 2008 global financial crisis. While previous research has analysed the advantages, drawbacks, and methods of open innovation, less is known about how firms adjust their open innovation strategy in response to major economic shocks. Guided by theories of organisational learning and behavioural theory of the firm, we examine the impact of demand shock on firm openness to external knowledge. To test our hypotheses, we analyse a unique dataset on innovation in Swiss firms during the financial crisis. Our findings show that firms persisted with open innovation during the crisis, but the nature of the shock had a differential effect on how firms searched for external knowledge. This research contributes to a better understanding of the role of open innovation in times of crisis and provides insights into how firms adjust their innovation strategies in response to economic shocks., Industry and Innovation, ISSN:1469-8390, ISSN:1366-2716

Empirical evidence suggests that the social effects of internal migration may be substantially different from those associated with the arrival of international migrants. In this paper, I provide the first evidence of the effect of internal migration on crime with longitudinal data from Brazilian microregioes . Using local labour demand shocks in the manufacturing sector as an instrument for migratory flows, I find that a 10 per cent increase in the in-migration rate translates into a 6 per cent increase in the homicide rate in destinations.

Under what conditions do high levels of export concentration in a single market create vulnerability to coercive economic power? This paper examines that question through a detailed examination of the experiences of Australian export industries that lost access to the Chinese market during a recent and ongoing sanctions episode that began in May 2020. We characterize sanctions as government interventions that distort free economic exchange, and ask how markets autonomously adjust to these shocks. Despite China being a large and highly valuable export market for many affected industries, the economic – and accordingly political – impacts of sanctions have been more modest than anticipated. The reason for this lies in market adjustments. Theoretically, we extend insights from extant research on how market dynamics condition the impact of sanctions that generate ‘supply shocks’ (such as oil embargoes) to the new domain of ‘demand shocks’, modeling the process of responding to unilateral import sanctions from the perspective of export industries in a target state. We argue that losses can be diminished by three mechanisms that are understudied in the sanctions literature: trade reallocation (where buyers and sellers shift but do not lose trade partners); trade deflection (circumventing sanctions via intermediaries); and product transformation (the transformation of production processes to produce and sell entirely different products or similar products not covered by sanctions). Empirically, we describe variation in the adjustment processes undertaken in nine Australian industries affected by the loss of the Chinese market, and explore the conditions under which these adjustments are more or less viable, depending upon differences in market structures and dynamics across products.

Using loan-level data covering two-thirds of all corporate loans from U.S. banks, we document that SMEs (i) obtain much shorter maturity credit lines than large firms; (ii) have less active maturity management and therefore frequently have expiring credit; (iii) post more collateral on both credit lines and term loans; (iv) have higher utilization rates in normal times; and (v) pay higher spreads, even conditional on other firm characteristics. We present a theory of loan terms that rationalizes these facts as the equilibrium outcome of a trade-off between commitment and discretion. We test the model's prediction that small firms may be unable to access liquidity when large shocks arrive using data on drawdowns in the COVID recession. Consistent with the theory, the increase in bank credit in 2020Q1 and 2020Q2 came almost entirely from drawdowns by large firms on pre-committed lines of credit. Differences in demand for liquidity cannot fully explain the differences in drawdown rates by firm size, as we show that large firms also exhibited much higher sensitivity of drawdowns to industry-level measures of exposure to the COVID recession. Finally, we match the bank data to a list of participants in the Paycheck Protection Program (PPP) and show that SME recipients of PPP loans reduced their non-PPP bank borrowing in 2020Q2 by between 53 and 125 percent of the amount of their PPP funds, suggesting that government-sponsored liquidity can overcome private credit constraints.

This paper analyzes a two-good economy wherein an efficiency wage is paid. Our objective is to determine how outputs, employment, and unemployment will change in response to both exogenous demand and supply shocks. Our principal conclusion is that demand shocks cannot explain decreases in production in both sectors of such an economy. The driver of this and our other conclusions is the role of relative prices in determining supply, and the labor market linkages between sectors.

I propose an explanation for the positive relation between R&D, future earnings, and future stock returns based on the fixed-cost qualities of R&D. If R&D is relatively fixed over short horizons, demand shocks realized by some R&D firms will push these firms into R&D intensity levels that are suboptimal as common scale proxies—market equity, assets, and sales—respond more quickly to demand shocks than R&D. In response, R&D firms realizing negative demand shocks reduce future expenses and capital expenditures, producing higher future profitability on lower sales growth. Consistent with the fixed-cost hypothesis, I find the higher future profits of high R&D firms are explained by cost cutting, not revenue growth. Collectively, the restructuring of cost and capital structures of the subset of high R&D firms realizing demand shocks explains the future profit and investment patterns of R&D firms, while the fixed-cost qualities of R&D seem to explain patterns in future stock returns. My results have implications for literatures that examine how decisions on R&D investment levels affect future firm performance, growth, and stock returns.

We investigate how demand conditions affect employers’ provision of safety—something about which theory is ambivalent. Positive demand shocks relax financial constraints that limit safety investmen...

The research aims to examine the vulnerability and resilience of road transport enterprises in Poland to a crisis caused by the COVID-19 pandemic. In theory, we refer to the Schumpeterian perspective of creative destruction. In the empirical analysis, survey data on 500 transport companies randomly selected from the database were used. We estimated partial proportional odds models to show the factors responsible for the enterprises' vulnerability and resilience to unforeseen shock. The perspective refers to the total sample size and the division into two subgroups: micro and small and medium enterprises. To justify the results, we calculated a set of statistical indicators and tests. These models enable separating enterprises according to the vulnerability level. Transport enterprises occurred significantly vulnerable to the COVID-19 crisis, particularly the demand shock. The only factor that influenced resilience was the decrease in fuel prices, which allowed a cost reduction. The crisis showed that government aid was helpful in the short run, particularly for micro and small enterprises. The medium-sized enterprises were more resilient than micro and small ones. We formulated several recommendations to help transport enterprises to adjust in the medium term.

The cyclical behavior of markups is at the center of macroeconomic debate on the origins of business-cycle fluctuations and policy effectiveness. In theory, markups may fluctuate endogenously with the business cycle due to sluggish price adjustment or to deeper motives affecting the price-elasticity of demand faced by individual producers. In this article we make use of a large firm- and product-level panel of Portuguese manufacturing firms in the 2004-2010 period. The biggest empirical challenge is to separate supply (TFP) from demand shocks. Our dataset allows to do so, by containing information on product-level prices at a yearly frequency. Furthermore, markups are mismeasured when calculated with the labor share. We use the share of intermediate inputs instead. Our main results suggest that markups are pro-cyclical with TFP shocks and generally counter-cyclical with demand shocks. We also show how markups become procyclical if the markup is obtained using the labour share instead of intermediate inputs. Adjustment costs create a wedge between the labour share and the actual markup which explain the observed correlations. JEL codes: C23, E32, L16, L22

We study how the public changes their mobility and retail spending patterns as precautionary responses to the disclosed location of COVID-19 cases. To look into the underlying mechanisms, we investigate how such change varies spatially and whether there is any spatial spillover or substitution. We use the daily data of cell phone?based mobility and credit card transactions between February 10 and May 31 in both 2019 and 2020 in Seoul, South Korea, and employ the empirical approach analyzing the year-over-year percent change for the mobility and consumption outcomes. Results report that one additional COVID-19 case within the last 14 days decreased non-resident inflow and retail spending by 0.40 and 0.65 percentage points, respectively. Then, we also find evidence of spatial heterogeneity: the mobility and retail performances of neighborhoods with higher residential population density were more resilient to COVID-19 case information while neighborhoods with higher levels of land use diversity and retail agglomeration experienced a greater localized demand shock. This heterogeneity is not negligible. For example, one additional COVID-19 case in neighborhoods in the bottom 20% for population density led to a decline of 1.2 percentage points in retail spending, while other neighborhoods experienced a less negative impact. Finally, we find a significant spatial spillover effect of disclosed COVID-19 information instead of spatial substitution. One additional COVID-19 case in geographically adjacent areas within the last 14 days reduced non-resident inflow and retail spending in the subject neighborhood by 0.06 and 0.09 percentage points, respectively. This article is protected by copyright. All rights reserved.

Rising current account imbalances around the globe preceded the Great Recession in the late 2000s. These imbalances narrowed significantly during the crisis mainly due to a negative demand shock and plummeting imports in deficit countries. While income inequality and household debt played a pivotal role in current account imbalances prior to the crisis, it is unclear whether these relations still hold when including the post-crisis era. We estimate current account determinants using a panel of 31 OECD countries over 45 years and include measures for functional and personal income distribution as well as household debt. We find a sustained relation between income inequality and current accounts when including the post-crisis period, while the link to household debt diminishes, indicating a change in the debt regime in a number of countries.

The study aimed at determines the impact of COVID 19 on the Arab countries using the Bayesian Vector Auto-regressions model PVAR, and determines the economic policies and mechanisms that can be taken to limit the repercussions of Corona on the Arab countries. The findings revealed the breakups of the Arab economies; COVID 19 was a supply shock in its first-time impact, but quickly trans-passes to demand shock. the pandemic effect decreases employment, exports and government expenditure, but investment and imports decline up then show a slight increase, and results a massive rise in consumer price index then a slight decrease. The study also relies on the SWOT Analysis method to analyze the repercussions of Coronavirus on economies of the Arab countries through analyzing the internal environment, by monitoring strengths and weaknesses, and analyzing the external environment by monitoring opportunities and threats. There is a necessity for a help of bilateral creditors and the international financial institutions for the Arab countries. The international community needs to intensify financial aid to many emerging market and developing economies.

Which are the effects of pandemics on the returns to factors of production? Are these effects persistent over time? These questions have received renewed interest after the out-burst of deaths caused by Covid-19. The Spanish Flu is the closest pandemic to Covid-19. In this paper, we analyze the impact of the Spanish Flu on the returns to labor and capital in Spain. Spain is an ideal country to perform this exercise. First, the “excess death rate” was one of the largest in Western Europe and it varied substantially across regions. Second, Spain was transitioning towards industrialization, with regions in different stages of development. Third, Spain was developed enough to have reliable data. We identify the effect of the Spanish Flu by exploiting within-country variation in “excess death rate”. Our main result is that the effect of the Spanish Flu on daily real wages was large, negative, and broadly short-lived. The effects are heterogeneous across occupations and regions. The negative effects are exacerbated in (i) occupations producing non-essential goods like shoemakers and (ii) more urbanized provinces. Quantitatively, relative to pre-1918, the decline for the average region ranges from null to around 30 percent. In addition, we fail to find significant negative effects of the flu on returns to capital. Whereas the results for dividends are imprecisely estimated (we cannot reject a null effect), the effect on real estate prices (houses and land), driven by the post-1918 recovery, is positive. Experts on inequality have argued that pandemics have equalizing effects especially in a Malthusian setting, due to real wage increases. Our findings suggest that, at least, for a developing economy like Spain in the early 20th century, this result does not apply. Indeed, we document that the flu pandemic was conducive to a (short-run) reduction in real wages. In addition, we interpret our heterogeneous results as suggestive evidence that pandemics represent a demand shock.

Do firearm purchase delay laws reduce aggregate homicide levels? Using variation from a 6-month countrywide gun demand shock in 2012/2013, we show that U.S. states with legislation preventing immediate handgun purchases experienced smaller increases in handgun sales. Our findings indicate that this is likely driven by comparatively lower purchases among impulsive consumers. We then demonstrate that states with purchase delays also witnessed comparatively 2% lower homicide rates during the same period. Further evidence shows that lower handgun sales coincided primarily with fewer impulsive assaults and points towards reduced acts of domestic violence.

This paper provides a novel perspective to the nexus of oil prices and stock markets by examining the impact of oil price shocks on stock market anomalies. After decomposing oil price shocks into three types (Kilian, 2009), we find that aggregate demand shocks have the strongest influence on stock market anomalies. In contrast, oil supply shocks and oil specific demand shocks have little impact. Similar results are also found in the industry analysis. Interestingly, the link between aggregate demand shocks and anomalies are the strongest among firms with either small size or high idiosyncratic risks. The documented effects are robust after controlling for investor sentiment as well as several well-known macroeconomic or market factors. Our findings are consistent with but also extend the results of Stambaugh, Yu, and Yuan (2012) in that we show that uncertainty also plays a role in explaining stock market anomalies.

In this paper we identify demand shocks that can have a permanent effect on output through hysteresis effects. We call these shocks permanent demand shocks. They are found to be quantitatively important in the United States, in particular when the Great Recession is included in the sample. Recessions driven by perma- nent demand shocks lead to a permanent decline in employment and investment (including R&D investment), while output per worker is largely unaffected. We find strong evidence that hysteresis transmits through a rise in long-term unemployment and a decline in labor force participation and disproportionately affects the least productive workers.

We study whether two groups of mental health care providers—each paid according to a different payment scheme—adjusted the duration of their patients' treatments after they faced an exogenous 20% drop in the number of patients. For the first group of providers, self-employed providers, we find that they did not increase treatment duration to recoup their income loss. Treatment duration thresholds in the stepwise fee-for-service payment function seem to have prevented these providers to treat patients longer. For the second group of providers, large mental health care institutions who were subject to a budget constraint, we find an average increase in treatment duration of 8%. Prior rationing combined with professional uncertainty can explain this increase. We find suggestive evidence for overtreatment of patients as the longer treatments did not result in better patient outcomes, i.e. better General Assessment of Functioning scores.

Purpose In examining an economic fluctuation, researchers often refer to the theories of impaired access to capital which mostly explain, from the perspective of bank lending supplies, a shock in firm’s access to investment would decrease its capital expenditures and net debt issuance during crisis period. However, some studies show that this is not always the case. A demand shock theory can explain the decrease in firm’s capital expenditures and net debt issuance during crisis period, but there should be no causal link between the two. This is because firms naturally do not invest during crisis period because of a decrease in investment wealth during crisis period. This paper aims to examine these theories with respect to the Covid-19 crisis in Indonesia. Design/methodology/approach The change in firms’ capital expenditure and net debt issuance is analyzed using a non-parametric difference-in-difference and matching estimator across four firm-dimensions to see whether the implications of the supply shock theory apply to the current crisis or if that firms naturally do not invest during the crisis. In addition, this paper provides the result of panel regression to confirm the causal link between firms’ investment funds and capital expenditure, with an addition of consumer confidence index to accommodate the implications of the demand shock theory. Findings The results of this paper show that the implications of the supply shock theory cannot explain the economic fluctuation during the Covid-19 crisis. Rather, the results suggest that firms naturally do not want to invest during the crisis and that the demand shock can better explain the economic fluctuation during the Covid-19 crisis. This is confirmed by the result of panel regression which shows that only consumer confidence index has a significant positive relationship with firms’ capital expenditure. Originality/value This is the first study to examine the theory of impaired access to capital with respect to the Covid-19 crisis in Indonesia.

We study a hybrid system where the demand of customers can be satisfied by both manufacturing new products and remanufacturing used products. To manage the serviceable inventory, we implement a proportional order-up-to (POUT) replenishment policy. In this context, we first analyse the system efficiency by assessing its capacity to meet customer demand in a cost-effective manner. To this end, we consider both inventory performance (i.e., the balance between inventory holding and stock-out costs) and production smoothness (by measuring the Bullwhip effect in the supply chain). Second, we investigate the system resilience to demand volatility. In particular, we explore the impact of demand shocks on the inventory and production of the closed-loop system. Interestingly, we find that tuning the POUT controller to optimise efficiency may be problematic in terms of resilience to demand shocks. In this sense, a key trade-off exists that needs to be carefully considered by supply chain managers. Linking efficiency to resilience in such supply chains thus becomes essential to strengthen the transition towards more circular economic models. All in all, our analysis, via control-theoretic and simulation techniques, provides professionals with valuable insights into how to identify the appropriate ‘formula’ for building both efficient and resilient closed-loop supply chains.

The article examines business models for mixedmode (combined) passenger transportation and development of combined passenger transportation as a factor in the growth of capacity of the railway passenger transportation market. The crisis in the transport services market, caused by non-economic factors (COVID‑19 pandemic), is characterized by a classic combination of supply shocks and demand shocks for passenger transportation, which increases relevance of the problem of searching ways to rise the volume of passenger traffic, in particular, by rail, demand for services provided to the public using railway assets.The current approach to increasing the demand for railway passenger transportation by developing the railway route network, improving the equipment of railway stations and the quality of service, expanding the range of services offered, promoting everything that encourages the consumption of services by a larger number of customers, will remain important. Nevertheless, this approach should be critically considered and supplemented in the light of new economic trends motivated by digital technology. That is especially important today, when, in conditions of resource constraints, a strategic organisational solution is needed aimed at scaling a business, achieving an optimal «balance» of costs, quality, competencies, flexibility and customer focus.The organisation of combined passenger transportation involves active «horizontal» interaction of various transport organisations, both among themselves and with different cohorts of passengers with their own consumer preferences and income restrictions. Therefore, the transition from linear business processes built «vertically» to horizontal business processes that offer specialised packages of services through a «single window» system according to uniform standards based on digital technologies is relevant.The article proposes models for organising network interaction of participants in the passenger transportation market based on digital technologies to ensure «seamless» mobility of the population with the consolidating role of railway transport. Specific models for organising combined railway transportation should be based on a specific business model, the choice of which is determined by a strategic decision of the company.

Non-tariff measures (NTMs) are a prominent feature of many recent free trade agreement (FTA) negotiations. The implementation of NTMs within computable general equilibrium (CGE) models has been relatively simple to date, with modelers generally incorporating NTMs as tariff equivalents via export or import taxes or as import-augmenting technological (iceberg) change. Our study compares and contrasts two new methods with the traditional mechanisms used. The first new method is the willingness to pay method developed by Walmsley and Minor (2020); and the second, introduced here, provides a new mechanism for adjusting the exporters’ production costs directly, referred to as the export cost method. We find that the choice of mechanism can have important consequences for the estimated impact of changes in NTMs, with mechanisms that raise productivity leading to larger changes in real GDP than those that treat NTMs as associated with economic rents or demand shocks. We emphasize the importance of careful consideration being given to the nature of the NTMs being investigated, the econometric estimates of the associated trade costs, and the CGE model mechanisms being used to assess the impacts of changes in NTMs.

We examine firms’ employment adjustments immediately after the imposition of stringent lockdown in March 2020. In doing so, we use monthly administrative data, and take value-added tax payment changes as a proxy for the demand shock. We merge data with COVID-19 tests, classified by economic activity, and employ a fixed effects instrumental variable regression. We find that all sized firms in the manufacturing sector reduced employment more if they had uncovered tax liabilities before the lockdown. Among small firms, real estate and service sector firms downsized more rapidly. While employment changes are rather modest, this very early evidence points to the need to address liquidity needs and firm pre-conditions among capital-intensive and services firms and, in particular, small businesses, to avoid employment losses. Plain English Summary The administrative data from the first COVID-19 lockdown in 2020 point to the need to address liquidity requirements among manufacturers, capital-intensive and service firms, and, in particular, small businesses to avoid subsequent employment losses. While there is a vast literature on firms’ adaptation and adjustments in the face of adverse shocks, firms’ reactions and the macroeconomic implications of stringent, government-imposed lockdowns are much less understood due to their novelty. We analyze businesses’ responses to the first and very stringent lockdown in March 2020 by making use of monthly administrative data and taking value-added tax payment changes as a proxy for the demand shock. We exploit variation in the sectoral differences across small, medium, and large firms. A simple average employment adjustment was non-negative in agriculture, construction, information and communication, and public administration sectors in our sample. By merging data with COVID-19 tests, classified by economic activity, and employing a fixed-effects instrumental variable regression, we find that all sized firms in the manufacturing sector reduced employment more if they had uncovered tax liabilities before the lockdown. Among small firms, real estate and service sector firms downsized more rapidly. While employment changes are rather modest, this very early evidence about businesses’ reactions to COVID-19-induced uncertainty and activity restrictions points to the need to address business liquidity needs early on. Another policy message concerns the importance of firm pre-conditions among capital-intensive and services firms and, in particular, small businesses to avoid subsequent employment losses.

The recent coronavirus pandemic (COVID-19) has negatively impacted the whole economy, especially the oil industry, in at least two ways. First, it created a demand shock as COVID-19 reduced global demand for crude oil, increased uncertainty, and triggered a serious economic recession in most developed and emerging countries. Second, it led to a supply shock as the pandemic resulted in an oil trade war between the major oil-producing nations (Saudi Arabia and Russia). Both shocks led to very high levels of oil price volatility. Our paper explores the dynamics of this volatility and explains the effects of these two shocks (induced by an adjustment of oil demand and supply) on West Texas Intermediate (WTI) crude oil price volatility. Accordingly, we show that oil price volatility reacted substantially to the pandemic-induced oil shocks. In particular, we document the impact of uncertainty caused by these shocks and investor anxiety on oil price volatility. We show that greater uncertainty leads to more oil price volatility. Our findings remained unchanged even after controlling for modeling robustness.

PurposeThis study aims to measure the relationship between demand and exchange rate shocks in the tourism industry.Design/methodology/approachA panel data set is constructed covering the period between 1995 and 2017, and the data set includes the top 26 countries that host 10 million tourists and above in the world as of 2017. The standard errors of the series are used as an indicator of shocks. First, the cross-sectional dependency, stationarity and the homogeneity of the series are examined; second, a panel cointegration analysis is implemented; third, long-term panel cointegration coefficients are analyzed with Dynamic Common Correlated Effects (DCCE) approach; and, finally, Dumitrescu and Hurlin’s (2012) Granger non-causality test is used to detect the causality.FindingsThe preliminary analyses show that the variables are cross-sectional dependent and heterogeneous and are stationary in their first difference; hence, the effects of the shocks are temporary. On the other hand, as a result of the panel cointegration analysis, it is found that both series are cointegrated over the long-term. However, the long-term coefficients estimated with the DCCE approach are found not to be statistically significant. Finally, as a result of the Dumitrescu and Hurlin’s (2012) Granger non-causality test, it is concluded that there is a causality running from exchange rate shocks to demand shocks.Originality/valueTo the best of the authors’ knowledge, the cointegration between the tourism demand shocks and exchange rates shocks has not been investigated before, and therefore, this study is considered to be a pioneering study that will contribute to the literature.

Investor sentiment plays a significant role in asset prices, and sieves out safer and speculative stocks, and captures institutional and retail investors’ demand shocks. Previous studies focus on the effects of investor sentiment in the developed stock markets using various sentiment metrics. We propose overnight and over-weekend returns as firm-specific investor sentiment (FSIS) to reflect retail investors’ beliefs about the developing Chinese stock market, and show that FSIS has short-term persistence, a negative relation with intraday returns and price impact, a U-shaped relation with trading activity, an inverse U-shaped relation with long-run performance and a positive impact on cross-sectional returns. FSIS captures the characteristics of the Chinese stock market with short-selling constraints, and market-level information of FSIS explains risk premiums from sentiment-driven mispricing. Our results also reflect the stronger-self remediability after the 2015 crash of the Chinese stock market.

The beer industry in the United States is in a period of dramatic transformation. Major breweries are acquiring much smaller craft breweries in an attempt to purchase growth, but it is not clear whether these acquisitions are economically viable. In this paper, we study the impact of craft brewery acquisitions on retail beer prices, and firm profitability in a dynamic, Markov‐perfect equilibrium pricing framework. We find that the estimated impact of mergers, or buyouts, is critically dependent upon estimates of the extent of state‐dependence in demand and is, in fact, negatively correlated with the initial shock to demand. That is, if the demand shock is positive, the effect of a buyout will be under‐estimated by not accounting for state‐dependence in demand, while it is over‐estimated if the demand shock is negative. This finding is intuitive as the static model will not properly account for the long‐term positive effects of a demand shock that is initially positive, or the long‐term negative effects that are initially negative. Ultimately, we show that not all the craft‐beer buyouts in 2015 made economic sense from the acquirer's perspective. [EconLit Citations: D43, L13, M31].

We revisit the discussion about the relationship between price’s cyclical features, implicit collusion and the demand level in an oligopoly supergame where a positive shock may hit demand and disrupt collusion. The novel feature of our model consists in characterising the post-shock noncooperative price and comparing it against the cartel price played in the last period of the collusive path, to single out the conditions for procyclicality to arise both in the short and in the long-run. This poses an issue in terms of an antitrust agency’s ability to draw well defined conclusions on the firms’ behaviour after the occurrence of the shock, with particular reference for the litigation phase after a cartel breakdown.

We consider the pricing problem faced by a revenue-maximizing platform matching price-sensitive customers to flexible supply units within a geographic area. This can be interpreted as the problem faced in the short term by a ride-hailing platform. We propose a two-dimensional framework in which a platform selects prices for different locations and drivers respond by choosing where to relocate, in equilibrium, based on prices, travel costs, and driver congestion levels. The platform’s problem is an infinite-dimensional optimization problem with equilibrium constraints. We elucidate structural properties of supply equilibria and the corresponding utilities that emerge and establish a form of spatial decomposition, which allows us to localize the analysis to regions of movement. In turn, uncovering an appropriate knapsack structure to the platform’s problem, we establish a crisp local characterization of the optimal prices and the corresponding supply response. In the optimal solution, the platform applies different treatments to different locations. In some locations, prices are set so that supply and demand are perfectly matched; overcongestion is induced in other locations, and some less profitable locations are indirectly priced out. To obtain insights on the global structure of an optimal solution, we derive in quasi-closed form the optimal solution for a family of models characterized by a demand shock. The optimal solution, although better balancing supply and demand around the shock, quite interestingly also ends up inducing movement away from it. This paper was accepted by David Simchi-Levi, optimization.

Purpose This paper aims to examine the impact of the daily growth rate of COVID-19 cases in the USA (COVIDg), the Federal Fund Rate (FFR) and the trade-weighted US dollar index (USDX) on S&P500 index daily returns and its 11 constituent sectors’ indices for the time period between January 22, 2020, until June 30, 2020. Design/methodology/approach The study uses the multivariate generalized autoregressive conditional heteroscedasticity (MGARCH) model to gauge the impacts over the whole period of study, as well as over two sub-periods; first, January 22, 2020, until March 30, 2020, reflecting uncertainty in the US markets and second, from April 1, 2020, until June 30, 2020, reflecting the lockdown. Findings Results of the MGARCH model reveal a negative and significant relation between COVIDg and S&P500 index daily returns over the first sub-period and the whole study period in the following sectors, namely, communications, consumer discretionary, consumer staples, health, technology and materials. Yet, COVIDg showed a positive and significant relation with S&P500 index daily returns during the second time period in the following sectors, namely, communication, consumer discretionary, financial, industrial, information technology (IT) and utilities. Besides, USDX showed a negative significant effect on S&P500 index daily returns and on the daily return on each of its 11 constituent sectors over the second sub-period and the whole period. Further, FFR showed a significant effect only in the second sub-period, specifically, a negative effect on the daily return of the financial sector and a positive effect on the daily return of the technology sector index. Nevertheless, FFR had a positive significant effect on the daily return of the utilities sector index for the whole period under study. Research limitations/implications The impact of the crisis on the S&P500 index can be assessed only with some limitations owing to available global data and the limited time frame of the lock-down. Practical implications The study proposes supporting a smooth, functioning and resilient financial system; increasing fiscal measures by the US Government to increase liquidity on constraints; measures by The Federal Reserve to alleviate US dollar funding shortages; support market integrity; ensure continuous transparency and sharing of information; support the health sector, as well as consumer-based sectors that faced demand shocks and facilitate investments in the technology sector. Originality/value The originality of this paper lies in the examination of the impact of the novel COVID-19 pandemic on each of the 11 sectors constituting the S&P500 index separately, reflecting how the main economic sectors formulating the US economy reacted to the shock during the peak time of the pandemic to observe a full picture of the economic consequences amid the pandemic.

This paper explores the properties of dynamic aggregate housing models. In conventional models, in response to demand shocks the primary adjustment mechanism is through prices and changes in housing supply. However, the size of the supply response depends on the price elasticity of supply and in countries such as the UK where the elasticity is low, house prices can rise sharply, worsening affordability. But this ignores the roles of housing risk and credit markets which affect the user cost of capital and the paper demonstrates that models that explicitly introduce a housing risk premium have an additional price stabiliser. The importance is shown through stochastic simulations; these simulations also demonstrate that conventional models used for forecasting and policy analysis may overstate future house price growth.

This paper analyses the socio-economic impact of the noble Corona virus (COVID-19) on ‘Middle East and North Africa’ (MENA) region as well as the role and opportunities of Islamic finance post COVID-19. The findings show that pandemic has affected the MENA region massively like any other region in the world. Since around 69% of the word’s crude oil supply is from this region alone, this causes it to suffer from dual shocks of COVID-19 pandemic as well as the declining crude prices that is caused by shocks from both ends, negative supply shock and a negative demand shock. The 19 countries in MENA region include from some of the richest countries of the world such as, Qatar, Kuwait, and Saudi Arabia, to some of the most vulnerable, poor and war ridden countries like Yemen, Syria, and Morocco. To mitigate the adverse effects of the pandemic, we suggest some immediate actions that can be taken such as a public fund to support health system, financial support to individuals and SME’s, financial support to corporations in order to prevent job loss and layoff and assurance of liquidity in domestic markets to prevent liquidity crunch. Finally, the paper analyses the role of Islamic finance in the region in recovery post COVID-19 and show that Islamic finance can be utilized as an alternative financial system in providing the relief to the COVID-19 affected people and entrepren

We argue that information accumulation provides a quantitatively successful propagation mechanism that challenges and empirically improves on the conventional New Keynesian models with many nominal and real rigidities. In particular, we build a tractable heterogeneous-firm business cycle model where firms face Knightian uncertainty about their profitability and learn it through production. The feedback between uncertainty and economic activity maps fundamental shocks into an as if procyclical equilibrium confidence process, generating co-movement driven by demand shocks, amplified and hump-shaped dynamics, countercyclical correlated wedges in the equilibrium conditions for labor, risk-free and risky assets, and countercyclical firm-level and aggregate dispersion of forecasts.

This article examines how monetary policy responses to economic shocks and monetary policy effectiveness have changed in the Philippines since inflation targeting was implemented in 2002. The study makes use of a structural vector autoregression to estimate financial and monetary policy shocks, among other shocks, based on an identification strategy similar to Gilchrist and Zakrajsek [2012] and Bassetto et al. [2016]. A Philippine financial conditions index (FCI) purged of monetary influences then decomposed according to instrument or market is used to aid estimation and analysis. Results of the recursive vector autoregressions (VAR) comparing pre-inflation-targeting and inflation-targeting periods reveal stronger and more systematic policy responses to non-financial demand shocks, partial and transitory accommodation of supply shocks, and greater exchange rate flexibility initially under the new monetary policy regime. There is, however, an observed weakening of monetary policy responses to financial disturbances and monetary policy transmission to growth likely related to episodes of strong capital inflows. JEL classification: C32, E31, E42, E44, E52, E58