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In the past three decades, Cuba has extended opportunities for Multinational Enterprises (MNEs) to establish operations within its predominantly centrally planned economy. Many MNEs have seized this opportunity and established their presence in Cuba, resulting in FDI inflows reaching up to 2 per cent of GDP in certain years. In our paper, we aim to assess the impact of MNEs' activity on local companies, with a specific focus on productivity spillover effects. Additionally, we analyze how institutional factors influence the strength of these effects. Our data collection involved conducting questionnaires and semi-structured interviews with MNEs operating in Cuba and experts on the Cuban economy. Our findings reveal that MNEs introduce new technology and knowledge to Cuba, thereby positively influencing the local development. We have confirmed the existence of vertical spillover effects, as certain MNEs provide direct assistance to local companies with whom they collaborate. The extent of these spillover effects is heavily contingent on Cuba's institutional framework. Local regulations mandate that MNEs cooperate with local companies for various operations, such as expanding product distribution across the country, thus amplifying the impact. Conversely, spillover effects through labor mobility are limited, as there is a low rate of transition from MNEs to local companies among the local workforce. Stringent legal constraints further hinder interaction between MNEs and the Cuban private sector, thereby limiting the broader spillover effects. [ABSTRACT FROM AUTHOR]

Using daily data over the period August 5, 2013 – September 27, 2019, this study investigates the dynamic spillovers between international monetary policies across four major economies (i.e. Eurozone, Japan, UK and US) and three key cryptocurrencies (i.e. Bitcoin, Litecoin and Ripple). In doing so, we apply a Time-Varying Parameter Vector Auto-Regression (TVP-VAR) model, a dynamic connectedness approach and network analysis. The empirical results indicate that cryptocurrency returns and monetary policy spillovers were particularly large when shadow policy rates became negative, moderated during the Fed's 'tapering process', and sharpened again more recently as cryptocurrency buoyancy returned. Gross directional spillovers suggest that shadow policy rates have more 'to give than to receive', while those from and to cryptocurrency returns are naturally volatile. There is also strong interconnectedness between monetary policy in either the US or the Eurozone and the UK, and between Bitcoin and Litecoin. However, the spillovers across monetary policy and cryptocurrencies tend to be muted. Finally, spillovers were only slightly larger during the Fed's 'unconventional' policy compared to the 'standard' era, but their composition qualitatively changed over time. [ABSTRACT FROM AUTHOR]

Objectives: Little is known about whether the Oncology Care Model (OCM) affected care for non-Medicare patients. Study Design: The quasi-experimental design here compares participant providers with non-participant providers during the first year of the program compared with the prior year. Methods: Relative different levels of office visits and total costs across four cancers – breast, lung, colon, and prostate cancer – are measured for patients with Medicare Advantage, private insurance, and Medicaid and compared with the Medicare population. Results: OCM participation is associated with 11.6% fewer Medicare breast cancer visits (estimate = −0.11, 95% CI: −0.20 to −0.01, p = 0.03) and 9.3% fewer Medicaid breast cancer visits (estimate = −0.10, 95% CI: −0.21 to 0.02, p = 0.09). Practices seeing more Medicare patients drive this result; every 10 percentage points more Medicare patients seen by OCM providers correlate with 6.1% fewer Medicaid visits (estimate = −0.66, 95% CI: −1.39 to 0.06, p = 0.07). Some patterns like lower costs did not extend to non-Medicare patients while others absent in Medicare were measured in non-Medicare patients. Conclusions: This analysis suggests that care patterns are different under the OCM for both Medicare and non-Medicare lives, but that these differences are modest and inconsistent. [ABSTRACT FROM AUTHOR]

We develop a framework to analyze partial population experiments, a generalization of the cluster experimental design where clusters are assigned to different treatment intensities. Our framework allows for heterogeneity in cluster sizes and outcome distributions. We study the large-sample behavior of OLS estimators and cluster-robust variance estimators and show that (i) ignoring cluster heterogeneity may result in severely underpowered experiments and (ii) the cluster-robust variance estimator may be upward-biased when clusters are heterogeneous. We derive formulas for power, minimum detectable effects, and optimal cluster assignment probabilities. All our results apply to cluster experiments, a particular case of our framework. We set up a potential outcomes framework to interpret the OLS estimands as causal effects. We implement our methods in a large-scale experiment to estimate the direct and spillover effects of a communication campaign on property tax compliance. We find an increase in tax compliance among individuals directly targeted with our mailing, as well as compliance spillovers on untreated individuals in clusters with a high proportion of treated taxpayers. [ABSTRACT FROM AUTHOR]

This study examined the connectedness and propagation of risk in the South African equity sectors during the Global Financial Crisis (GFC), the European Debt Crisis (EDC), the US–China trade war, and the COVID-19 pandemic. Daily returns of nine Johannesburg Stock Exchange (JSE) super sectors were examined from 3 January 2006 to 31 December 2021. Applying the connectedness matrix and time-varying parameter vector autoregressive (TVP-VAR) model, in full sample and sub-periods, the study showed that dynamic total connectedness of the super sectors is high in absolute form (62%). Furthermore, it was found that the highest volatility connectedness was during the EDC (68.83%) and during the COVID-19 pandemic (68.57%), followed by the GFC (63.16%) and lastly the US–China trade war (42.09%), respectively. This suggests that the tendency for a systemic risk is highest during the EDC, COVID-19, and GFC periods, and lowest during the US–China trade war. The financial sector was the primary net-transmitter of shocks during the COVID-19 period, while the automobile and parts sector was the strongest net-transmitter of shocks during the GFC, EDC, and US–China trade war. Similarly, the strongest net recipient of shocks during GFC, EDC, and COVID-19 is the chemical super sector. The study concludes that there is a significant volatility connectedness among JSE super sectors. In addition, the JSE super sectors exhibit time-varying connectedness during extreme events. Moreover, the net-transmitter and net-receiver of shock do not change significantly during different crisis periods. The policy implications of the findings are highlighted in the concluding section. [ABSTRACT FROM AUTHOR]

We study the impact of different sources of global, regional and local uncertainty on the seven largest Scandinavian banks over the period 2005–2018. Using a spillover approach and network analysis, we find that Swedish banks are the main source of contagion in the region and spillovers tend to increase in times of heightened uncertainty. Global economic policy uncertainty, global financial uncertainty and local housing market uncertainty affect the Scandinavian banking sector the most. By contrast, geopolitical risk spillovers are limited. [ABSTRACT FROM AUTHOR]

This study develops new insights into the spillover effects of foreign multinational enterprises (MNEs) on local firms' export market entry, using the case of Vietnam—a notable global manufacturing hub located in Southeast Asia. The empirical analysis is based on a disaggregated firm‐level panel dataset of 25,032 observations of Vietnamese food processing firms during the period 2011–2016. The food processing industry is an essential part of the country's thriving manufacturing sector, with enormous potential for exports. The random‐effects Probit estimation results suggest that the presence of foreign MNEs significantly raises the likelihood that private local firms become exporters and thereby start integrating into global value chains. Further regressions reveal that foreign presence is also linked to higher export intensity among domestic firms, and that the magnitude of the estimated spillover effects is conditional on the specific measures of foreign MNE presence, the ownership structure in local industry, and the size of local firms. The findings highlight the considerable potential for foreign MNEs to influence local firms' export prospects and validate the policy efforts to attract foreign direct investment inflows to the examined industry. [ABSTRACT FROM AUTHOR]

We develop a nonparametric quantile panel regression model. Within each quantile, the quantile function is a combination of linear and nonlinear parts, which we approximate using Bayesian Additive Regression Trees (BART). Cross-sectional information is captured through a conditionally heteroscedastic latent factor. The nonparametric feature enhances flexibility, while the panel feature increases the number of observations in the tails. We develop Bayesian methods for inference and apply several versions of the model to study growth-at-risk dynamics in a panel of 11 advanced economies. Our framework usually improves upon single-country quantile models in recursive growth forecast comparisons. [ABSTRACT FROM AUTHOR]

The European Union Emissions Trading System (EU ETS) is designed to promote carbon reduction in a cost-effective and economically efficient manner. To meet their compliance requirements, participants within the EU ETS can either invest in carbon abatement, thereby improving their environmental performances, or purchase carbon allowances from the market. Our analysis aims to investigate the structural features of the EU ETS trade network of allowances and assess its robustness to spillovers propagated from energy commodities. We build the EU ETS trade network of allowances on a daily basis by leveraging a granular dataset comprising over 32k accounts that performed approximately 720k trades, involving more than 127 billion of allowances from 2005 to 2020. Importantly, our analysis is able to cover entirely the first three phases of the EU ETS, thus providing an updated view on the functioning of the EU ETS. We find that the EU ETS trade network of allowances is disassortative and characterized by very active nodes belonging to the energy sector. Moreover, we detect that energy commodity transmission channels can be substantial and may shape the way nodes transfer allowances, with the configuration of the EU ETS often being a net receiver of spillovers. These findings are robust even when we analyze extreme quantiles of the distribution to account for distressed periods. Our study shows how the functioning of the EU ETS can be influenced by spillovers imported from energy commodity markets. We discuss how investors can build portfolios that either hedge or amplify the impact of such spillovers, depending on their risk appetite. Given that energy commodities are significant inputs in the production processes of energy firms—who are highly active participants in the trade network of allowances—analyzing market responses to shocks in energy commodities is crucial for the effective implementation of the policy. [ABSTRACT FROM AUTHOR]

Nine viruses of the bean common mosaic virus subgroup of potyviruses are major international crop pathogens, but their phylogenetically closest relatives from non-crop plants have mostly been found only in SE Asia and Oceania, which is thus likely to be their "centre of emergence". We have compared over 700 of the complete genomic ORFs of the crop pandemic and the non-crop viruses in various ways. Only one-third of crop virus genomes are non-recombinant, but more than half the non-crop virus genomes are. Four of the viruses were from crops domesticated in the Old World (Africa to SE Asia), and the other five were from New World crops. There was a temporal signal in only three of the crop virus datasets, but it confirmed that the most recent common ancestors of all the crop viruses were before inter-continental marine trade started after 1492 CE, whereas all the crown clusters of the phylogenies are from after that date. The non-crop virus datasets are genetically more diverse than those of the crop viruses, and Tajima's D analyses showed that their populations were contracting, and only one of the crop viruses had a significantly expanding population. dN/dS analyses showed that most of the genes and codons in all the viruses were under significant negative selection, and the few that were under significant positive selection were mostly in the PIPO-encoding region of the P3 protein, or the PIPO protein itself. Interestingly, more positively selected codons were found in non-crop than in crop viruses, and, as the hosts of the former were taxonomically more diverse than the latter, this may indicate that the positively selected codons are involved in host range determination; AlphaFold3 modelling was used to investigate this possibility. [ABSTRACT FROM AUTHOR]

In this article, we introduce a new command, xtsfsp, for fitting spatial stochastic frontier models in Stata. Over the last decades, stochastic frontier models have seen important theoretical progress via the incorporation of various types of spatial components. Models that can account for spatial dependence and spillovers have been developed for efficiency and productivity analysis, drawing extensive attention from industry and academia. Because of the unavailability of the statistical packages, the empirical applications of the new stochastic frontier models appear to be lagging. The xtsfsp command provides a procedure for fitting spatial stochastic frontier models in the style of Orea and Álvarez (2019, Journal of Econometrics 213: 556-577) and Galli (2023, Spatial Economic Analysis 18: 239-258), enabling users to handle different sources of spatial dependence. In this article, we introduce spatial stochastic frontier models, describing the syntax and options of the new command and providing several examples to illustrate its usage. [ABSTRACT FROM AUTHOR]

Climate change has added new dimensions of uncertainty associated with India's rice production. Previous research has explored the impact of climate variation on production and noted the interdependence among neighbouring regions. Using district-level data, we investigate two categories of spatial dynamics associated with the climate sensitivity of rice yield. First, we find evidence that supports previous research that yield is significantly influenced by the direct effects of monsoon maximum temperature and rainfall. The second category, capturing indirect effects, is novel because it provides additional insights into formal and informal networks that underpin the information flow on climate adaptation. Empirical evidence of spatial interdependence arising from information spillovers provides insights into the development of spatially targeted policies that offer the potential for knowledge transfer that contributes to sustaining and increasing rice yields. Policy objectives should therefore focus on advancing technology and promoting social networks that enhance information flow across regions. [ABSTRACT FROM AUTHOR]

Summary: This paper empirically investigates the propagation of firm expectations within the European Union (EU). To this end, we combine information from EU‐wide official business surveys with input–output data. Econometrically, we model interdependencies in economic activities via input–output linkages and apply space‐time models with common factors. The resulting evidence provides indication for the existence of substantial spillover effects in expectation formation. They are transmitted both upstream and downstream the European value chain, but the latter channel matters more. [ABSTRACT FROM AUTHOR]

Summary: We provide new evidence that the transmission of oil price shocks to the US economy has changed with the shale oil boom. To show this, we develop a time‐varying parameter factor‐augmented vector autoregressive (FAVAR) model with a large data environment of state‐level, industry, and aggregate US data. The model effectively captures potential spillovers between oil and non‐oil industries, as well as variation over time. Specified in this way, we find that investment, income, industrial production, and (non‐oil) employment in most oil‐producing and some manufacturing‐intensive US states increase following an oil‐specific shock—effects that were not present before the shale oil boom. [ABSTRACT FROM AUTHOR]

An important issue in economic evaluations is determining whether all relevant impacts are considered, given the perspective chosen for the analysis. Acknowledging that patients are not isolated individuals has important implications in this context. Increasingly, the term "spillovers" is used to label consequences of health interventions on others. However, a clear definition of spillovers is lacking, and as a result, the scope of the concept remains unclear. In this study, we aim to clarify the concept of spillovers by proposing a definition applicable in health economic evaluations. To illustrate the implications of this definition, we highlight the diversity of potential spillovers through an expanded impact inventory and conduct a mapping review that outlines the evidence base for the different types of spillovers. In the context of economic evaluations of health interventions, we define spillovers as all impacts from an intervention on all parties or entities other than the users of the intervention under evaluation. This definition encompasses a broader range of potential costs and effects, beyond informal caregivers and family members. The expanded impact inventory enables a systematic approach to identifying broader impacts of health interventions. The mapping review shows that the relevance of different types of spillovers is context-specific. Some spillovers are regularly included in economic evaluations, although not always recognised as such, while others are not. A consistent use of the term "spillovers", improved measurement of these costs and effects, and increased transparency in reporting them are still necessary. To that end, we propose a research agenda. [ABSTRACT FROM AUTHOR]

We analyse whether US federal aid to state and local governments impacted economic activity through either direct or cross-state spillover effects during the COVID-19 pandemic. Deploying an instrumental-variables framework rooted in the funding advantage of states that are over-represented in Congress, we find that federal assistance had significantly less impact on state and local government employment, as well as broader measures of economic activity, than estimates from prior crisis responses would imply. The modest employment impacts we find stem largely from the direct effect of states' own aid allocation, as opposed to spillovers across state lines. These findings point to an important role for variations in fiscal policy transmission mechanisms, namely that cross-state spillovers are less likely to be important when some of the key mechanisms for such spillovers, like robust interjurisdictional supply chains and patterns of consumption, are muted or shut down. [ABSTRACT FROM AUTHOR]

This paper proposes a structural decomposition analysis (SDA) augmented with cross-country atmospheric circulation and uncovers that changes in carbon monoxide (CO) levels are driven by atmospheric flows way more than by any of the traditional SDA components. Applied to a five-region model, our results show, among others, that South Korea has certainly been able to reduce the CO emissions in its own territory by 0.8Tg over 1990–2014 but up to 10.6Tg of CO flowing to its borders came from its upwind neighbor China. That amount was primarily driven by activities satisfying the growth of China's domestic demand, although changes in foreign demand and in the technology effect were not negligible. By quantifying the role of upwind countries in air pollution changes, our methodology allows us to identify more comprehensive global emission abatement policies than the consumer- or producer-focused approaches currently used. [ABSTRACT FROM AUTHOR]

Abstract The European Union Emissions Trading System (EU ETS) is designed to promote carbon reduction in a cost-effective and economically efficient manner. To meet their compliance requirements, participants within the EU ETS can either invest in carbon abatement, thereby improving their environmental performances, or purchase carbon allowances from the market. Our analysis aims to investigate the structural features of the EU ETS trade network of allowances and assess its robustness to spillovers propagated from energy commodities. We build the EU ETS trade network of allowances on a daily basis by leveraging a granular dataset comprising over 32k accounts that performed approximately 720k trades, involving more than 127 billion of allowances from 2005 to 2020. Importantly, our analysis is able to cover entirely the first three phases of the EU ETS, thus providing an updated view on the functioning of the EU ETS. We find that the EU ETS trade network of allowances is disassortative and characterized by very active nodes belonging to the energy sector. Moreover, we detect that energy commodity transmission channels can be substantial and may shape the way nodes transfer allowances, with the configuration of the EU ETS often being a net receiver of spillovers. These findings are robust even when we analyze extreme quantiles of the distribution to account for distressed periods. Our study shows how the functioning of the EU ETS can be influenced by spillovers imported from energy commodity markets. We discuss how investors can build portfolios that either hedge or amplify the impact of such spillovers, depending on their risk appetite. Given that energy commodities are significant inputs in the production processes of energy firms—who are highly active participants in the trade network of allowances—analyzing market responses to shocks in energy commodities is crucial for the effective implementation of the policy.

This paper investigates the adoption patterns of Leadership in Energy and Environmental Design (LEED) certification in China, analyzing data from 2010 to 2021. We find that builders' choices of certification levels are positively correlated within each province. However, for commercial buildings, builders differentiate from each other in the choice of certification levels. The study also identifies spatial spillovers of LEED certification across nearby provinces. We propose potential explanations for these findings and discuss their policy implications. The results suggest that the design of certification schemes should account for the strategic behavior of firms. Additionally, regional policies promoting green building certifications may have spillover effects, encouraging adoption in neighboring regions. [ABSTRACT FROM AUTHOR]

In this article, we compare a tax and a standard as environmental tools depending on firms' R &D strategy and the government's ability to credibly commit to its policy. We consider a duopoly model where production is polluting and in an effort to mitigate emissions, firms invest in green R &D (in the presence of technological spillovers) either cooperatively or non-cooperatively. We explore two policy games in which the regulator establishes an emission tax or an emission standard either before or after firms engage in R &D. We endogenize both the firms' R &D strategy and the regulator's choice of policy instrument. We find that an emission standard is adopted only when firms choose not to cooperate. Conversely, a tax is desirable when firms collaborate in green R &D. Moreover, we expand our framework by offering the opportunity for the regulator to authorize or ban cooperation in green R &D before the firms make their strategic decisions. [ABSTRACT FROM AUTHOR]

Abstract Objectives Recently, some developing countries are promoting foreign agricultural investments in Agriculture to exploit currently under-exploited land. Yet, the benefits to recipient countries remains less understood and inconclusive. The study sought to understand the association between proximity to a foreign agricultural investments (FAI) and adoption of soil and water conservation farming methods by smallholder farmers in Uganda. Methodology We used cross-sectional data collected from a total of 1,181 smallholder respondents, sampled through a multi-stage random sampling process resulting in three independent samples from South-western, Central and Northern Uganda. Using logistic regression analysis and pooled data, we study the association between proximity to a FAI and other factors that influence the adoption of soil and water conservation farming practices by smallholder farmers in Uganda. Results Descriptive results show that at the aggregate level proximity to a FAI, the education level of the farmer and ownership of information and communication assets (radio and mobile phone) are significantly different between adopter and non-adopters of soil and water conservation farming methods in the research area. The econometric findings of the study suggest that proximity to a foreign agricultural investments (FAI) has weak but significant spillovers on soil and water conservation farming practices of smallholder farmers it their vicinity with possible site specific variations that warrant more in-depth investigation. The effect of proximity to FAI on the adoption of soil and water conservation farming practices is complemented by the education level of the farmer and access to means of communication (radio, and in particular mobile phone set) indicating the importance of information and also broader socio-economic conditions. Recommendation We recommend policies that enhance increased exposure of smallholder farmers to FAI especially those that help promote rural digital penetration through increased band width, FM radios and affordable data packages.

In this study, we investigate how geographic proximity to industrial services provided by cities across the urban hierarchy contributes to differences in land prices of nearby towns. We construct three urban hierarchy tiers for cities in China based on their administrative levels. Using over 78,000 transaction data on the transfer of the land-use rights of industrial land between 2009 and 2019 from the China Land Market Network website, we observe spatial patterns in the spillover effect of industrial services. Land prices tend to decline with great distances from cities providing industrial services. Moreover, the spillover effects of urban service for the higher tiers of the urban hierarchy are large. Our results suggest that policymakers and urban planners should re-evaluate the agglomeration spillover effect because it may not fully consider the position of urban concentrations in the urban hierarchy.

We provide empirical evidence concerning dynamic persistence and spillovers in public expenditures with a focus on local governments. Using a unique panel dataset consisting of the counties and independent cities of Virginia, we find both time persistence and neighbour spillovers present in the data, but we find that time persistence is much stronger and reduces the strength of spatial spillovers by an average of 40% for different spending categories. We find that a spillover model is not well suited to local government expenditures due to mandatory spending. Time persistence captures the slow pace of many government activities. [ABSTRACT FROM AUTHOR]

The relationship between inward investments and local firms' productivity is contingent on several contextual conditions that collectively define the ability of firms and regions to recognise, assimilate and commercially apply external knowledge. Yet the empirical literature has been unable to account efficiently for such multidimensional sources of heterogeneous externalities. We introduce a novel two-stage empirical methodology that allows accounting for a wide range of moderating circumstances. Relying on a sample of 11,000 UK firms over the period 2012–2018, we show that while the nature of places affects the potential externalities from multinational enterprises (MNEs), what matters more are firm-level characteristics. This has important implications for regional policy, particularly in understanding the drivers of inequality, both within and across regions. [ABSTRACT FROM AUTHOR]

Although it is widely recognized that accounting for spillovers from higher education institutions is essential when formulating educational policy, research on these effects in developing countries is scarce. This study examines the spillover effects of Ethiopia's recent public university expansion program on the educational attainment of female adolescents in the surrounding areas. Employing an event study framework, the research demonstrates a positive association between the presence of a university in the neighborhood and the academic achievement of female students at lower educational levels. [ABSTRACT FROM AUTHOR]

Infill investments are argued to mitigate environmental footprints, regenerate places and accommodating population growth, but frequently generate local opposition. However, there is a dearth of knowledge around how different types of infill affect different segments of local property markets, how persistent effects are and how far they reach. Using detailed geocoded infill development activity and sales data, we test the price level and trajectory impacts of five infill types, distinguished by the net scale of additional dwellings, on property prices within five concentric 100-meter rings. Using an adjusted interrupted time-series estimation strategy with locality, property and neighborhood characteristic controls we find that developments that generate a net increase in dwellings of four or less, typically result in an appreciation in the average sales prices of proximate dwellings. Moderate and large-scale developments generate negative price effects, but these effects predominantly affect apartments and townhouses, not the dominant detached house submarket. Over time, amenity effects and local market potential may even have a further positive expectation effect on detached house prices. Infill type differentiation shows that urban densification may result in positive affordability outcome in the apartment submarket, but has the opposite effects in the detached house submarket. Divergent price trajectories also contribute to widening wealth disparities. [ABSTRACT FROM AUTHOR]

We investigate whether state health insurance parity laws adopted in the 1990s and 2000s for substance use disorder (SUD) treatment reduce traffic fatalities in the United States. Impaired driving is a major contributing factor to US traffic fatalities. State health insurance parity laws compel private insurers to cover SUD treatment more generously—on par with physical health services. We employ 21 years of administrative data from the Fatality Analysis Reporting System. We estimate both two-way fixed-effects regressions and an interaction-weighted estimator that is robust to potential bias attributable to heterogenous and dynamic treatment effects with staggered policy adoption. Our findings indicate that state parity law passage reduces overall traffic fatality rates by 2.8 percent, with larger effects for fatalities that involve alcohol. These findings suggest that state regulations requiring private insurers to equitably cover SUD treatment can improve traffic safety. [ABSTRACT FROM AUTHOR]

Leveraging on a new quarterly dataset of capital control adjustments, we find renewed evidence that the introduction or tightening of capital controls in one economy increases capital inflows to other similar borrowing economies, an effect often called capital flow deflection. However, not all flows are deflected alike. Capital flow deflection is primarily driven by portfolio investment and bank credit, and only controls targeting these types of flows generate this externality. Moreover, analysing bilateral capital flows in order to capture investing countries' characteristics, we find that capital controls tend to deflect flows from advanced economies' portfolio equity investors, while controls on bank‐related flows primarily deflects lending from emerging market banks. [ABSTRACT FROM AUTHOR]

In the past decades, intangibles assets have become an important source of productivity and economic growth in developed countries. Despite the transforming properties of intangibles across economies and the large and dynamic literature on the impact of intangible investments on productivity growth in frontier countries, there is not much evidence for the Latin America context. This paper contributes to the empirical literature on intangible investments along various dimensions. First, we make use of a large firm-level longitudinal data set from Peru, a Latin America middle income country, which contains separated information on intangible assets, which allow us to measure the impact of them on both wages and productivity at the firm level. Second, the analysis at the firm level and the panel structure of the data allows us to control for the endogeneity of variable inputs applying different control function approaches. In addition, the production function estimates provide us with a measure of unobservables, which we include in the wage equation to retrieve consistent estimates for the impact of intangible assets on wages. Third, our data allow us to explore how the impact of intangibles on wages and productivity is affected by the differences in the composition of the bundle of intangibles, changes in the product mix at the firm level and for the presence of imperfect competition in the labor market. We find that an increase in the share of intangible assets by one standard deviation is associated with 6.8% to 7.2% higher total factor productivity, depending on the model's specification. We also find that the capital productivity premium of intangible assets over tangible ones is substantial with estimates suggesting that intangibles are up to 2 times more productive than tangible assets. We also find that this capital productivity premium is not entirely offset by an increase in wages. Finally, we conclude that the main channels for appropriability are the specificity of the ideas generated by intangible investments at the firm level and the wage compression due to imperfect competition in the labor market. [ABSTRACT FROM AUTHOR]

This study examines the connectedness among eco-friendly assets and how volatility in fossil energy markets affects this connectedness. Using a broad coverage for eco-friendly assets such as a clean energy index, a clean cryptocurrency (Cardano), a green bond index, and a sustainability-leaders index, our results show that the connectedness is higher in the extremities (tail-risk spillovers) and more significant during essential world events such as a pandemic or war. Further, we employ nonparametric causality in quantiles, quantile regression, and kernel-based regularised least squares methods to investigate the influence of fossil energy markets (crude oil, natural gas, and gas oil) volatility on eco-friendly assets' connectedness. Our results imply that fossil energy market volatility has a positive and causal effect on connectedness dynamics among eco-friendly assets. Our study offers important implications for investors and policymakers in crafting portfolio strategies and policy decisions. [ABSTRACT FROM AUTHOR]

Emerging research indicates political corruption erodes political trust. However, previous studies have not adequately explored the question of whether corruption by a policy actor can spill over to influence trust in other policy actors. We draw insight from research and theory on collective reputation of organisations among other literature to explain why political corruption can produce reputational spillovers. Using individual-level Afrobarometer survey data from ten countries in the Southern African Development Community, one of the world's corruption hotspots, the analysis reveals perceived involvement in corruption by a policy actor can spill over to tarnish the reputation of other actors involved in the policy process. State and nonstate policy actors like politicians, judges, bureaucrats and traditional leaders in some measure share a collective reputation and fate. We offer suggestions on how to combat corruption in ways that minimise spillovers and safeguard a shared reputation. [ABSTRACT FROM AUTHOR]

This paper contributes to the ongoing debate on the nature and characteristics of the volatility transmission channels of major crash events in international stock markets between 03 July 1997 and 09 March 2021. Using dynamic conditional correlations (DCC) for conditional correlations and volatility clustering, GARCH-BEKK for the direction of transmission of disturbances, and the Diebold-Yilmaz spillover index for the level of volatility contagion, the paper finds that the climbs in external shock transmissions have long-lasting impacts in domestic markets due to the contagion effect during crisis periods. The findings also reveal that the heavier magnitude of financial stress is transmitted between Asian countries via the Hong Kong stock market. Additionally, the degree of volatility spillovers between advanced and emerging equity markets is smaller compared to the pure spillovers between advanced markets or emerging markets, offering a window of opportunity for international market participants in terms of portfolio diversification and risk management applications. Furthermore, the study introduces a novel early warning system created by integrating DCC correlations with a state-of-the-art deep learning model to predict the global financial crisis and COVID-19 crisis. The experimental analysis of long short-term memory network finds evidence of contagion risk by verifying bursts in volatility spillovers and generating signals with high accuracy before the 12-month crisis period. This provides supplementary information that contributes to the decision-making process of practitioners, as well as offering indicative evidence that facilitates the assessment of market vulnerability for policymakers. [ABSTRACT FROM AUTHOR]

This article analyzes spatial autocorrelations and the formation of clusters of exports, based on research and development (R&D) intensity in Portugal. The central idea is that exports show relative interdependence and spillover effects among nearby regions and a direct relationship with R&D expenditures. It adopts the new taxonomy of the OECD, separating exports by manufacturing and non-manufacturing activities by technological intensity. Methodologically, it applied exploratory spatial data analysis (ESDA), using global Moran's index and LISA. The results showed the presence of positive spatial autocorrelation of exports and the formation of a cluster of the high–high type for the Área Metropolitana do Porto and Região de Aveiro. There is also a positive spatial autocorrelation for exports associated with R&D expenditures as well as the formation of a regional cluster with high–high pattern for the Região de Aveiro. This outcome can be explained, in part, by nationally and internationally recognized universities and research centers surrounding the region, favoring knowledge spillovers across the regions. [ABSTRACT FROM AUTHOR]

This study employs a time-varying parameter vector autoregressive (TVP-VAR) model to investigate inflation propagation and spillovers among twelve major consumer prices components across eleven Euro area countries from 1999 to 2023. We uncover empirical regularities in the transmission channels of inflation, noting Transport and Clothing and Footwear as primary shock transmitters, whereas Communication, Alcohol and Tobacco consistently absorb shocks. These insights, consistent across various contexts and countries, contribute to understanding inflation persistence and households' inflation experiences in the Euro area and may contribute to more credible and effective policy design. [ABSTRACT FROM AUTHOR]

This study investigates the impact of geopolitical risk (GPR) on sustainable investments, focusing on five global environmental indices and two global GPR indices. Using Corrected Dynamic Conditional Correlation Generalised Autoregressive Conditional Heteroskedasticity (cDCC-GARCH) model and Diebold and Yilmaz's spillover analysis, we use daily data from January 2009 to October 2022, covering various market phases, including the European sovereign debt crisis, the COVID-19 pandemic, and the war in Ukraine. Results from the cDCC-GARCH model reveal high dynamic conditional correlations. During periods of high volatility, environmental indices displayed simultaneous and more intense responses, limiting investment diversification alternatives when considering only the environmental side. Diebold and Yilmaz's static analysis demonstrates that environmental segments are more influenced by systemic shocks than specific causes, with GPR's influence proving relatively weak. In the dynamic analysis, the spillover effects of GPR in environmental segments intensified during the pandemic crisis and the invasion of Ukraine, affecting market conditions. [ABSTRACT FROM AUTHOR]

IntroductionReconciling economic development and emission reduction of polluting gases requires balancing long-term and short-term goals across various markets. As a new production cost, the price of carbon allowances is assumed to affect the supply and demand of carbon-intensive sectors. Therefore, this study examines the dynamic price spillover effects between China as the largest carbon emission market and the carbon-intensive building materials industry in a unified time-frequency framework.MethodsThis study measures the dynamic overall and directional spillover effects of carbon and building materials markets in three frequency bands, considering eight carbon pilots and the national carbon market in China and four important building materials.ResultsThe empirical results show that the bi-directional spillover between carbon and the building materials market shows pronounced characteristics in the time-frequency domain, especially in the short-term frequency band of one day to one week, with strong connectivity. After the launch of the national carbon market, the information spillover from the building materials market to the carbon pilots become stronger. Both the carbon pilots and the national carbon market have significant short- and long-term impacts on the building materials market. In addition, there are differences in the impact of carbon markets on various types of carbon intensive building materials.DiscussionCompliance cycles in carbon markets are likely to induce sharp fluctuations in spillovers between the two markets. Therefore, balancing industrial development and stabilizing carbon prices requires a refined policy design that considers the diversified impacts of carbon markets on different industries at across frequencies.

This paper examines medium-term inflationary risks in the wake of the energy crisis. Firstly, the inflation spillovers between five major EU economies, viz. Germany, France, Italy, Spain, and Poland are analyzed using the Diebold and Yilmaz VAR framework. This analysis reveals that the interconnection between increases in inflation was stronger after the outbreak of the energy crisis. Poland and Spain have been transmitting inflation to the other countries under consideration. This impact is strongest when prices are “sticky”, i.e. when they are changed least frequently. Secondly, the impact of wage pressures in the Eurozone was analyzed with a special emphasis on the Netherlands on account of its historically high frequency of wage strikes. The data show that wage pressures from that country precede similar changes elsewhere in the eurozone. These two factors suggest that returning inflation to central bank targets in Europe is going to be a slow process.

Abstract Global economic downturns and multiple extreme events threaten Vietnam's economy, leading to a surge in stock market risk and significant spillovers. This study investigates market risk spillovers and explores the asymmetric effects of macroeconomic indicators on market risk across 24 sectors in Vietnam from 2012 to 2022. We use the value-at-risk (VaR) technique and a vector autoregression (VAR) model to estimate market risks and their spillovers across Vietnamese sectors. We then examine the asymmetric effects of macroeconomic indicators on market risk using a panel nonlinear autoregressive distribution lag (NARDL) model. Our results confirm that Vietnam’s market risk increases rapidly in response to extreme events. Additionally, market risks exhibit substantial inter-connectedness across the Vietnamese sectors. The Building Materials, Technology, and Securities sectors are primary risk transmitters, whereas the Minerals, Development Investment, and Education sectors are major risk absorbers. Our results also confirm that market risk responds asymmetrically to changes in interest rates, exchange rates (USD/VND), trade openness, financial development, and economic growth in the short and long run. Minerals, Oil & Gas, and Rubber are the sectors that are most affected by macroeconomic indicators in the long run. Based on these important findings, implications focused on limiting market risks and their spillovers, along with sustainable investing, have emerged.

Abstract This study uses high-frequency (1-min) price data to examine the connectedness among the leading cryptocurrencies (i.e. Bitcoin, Ethereum, Binance, Cardano, Litecoin, and Ripple) at volatility and high-order (third and fourth orders in this paper) moments based on skewness and kurtosis. The sample period is from February 10, 2020, to August 20, 2022, which captures a pandemic, wartime, cryptocurrency market crashes, and the full collapse of a stablecoin. Using a time-varying parameter vector autoregressive (TVP-VAR) connectedness approach, we find that the total dynamic connectedness throughout all realized estimators grows with the time frequency of the data. Moreover, all estimators are time dependent and affected by significant events. As an exception, the Russia–Ukraine War did not increase the total connectedness among cryptocurrencies. Analysis of third- and fourth-order moments reveals additional dynamics not captured by the second moments, highlighting the importance of analyzing higher moments when studying systematic crash and fat-tail risks in the cryptocurrency market. Additional tests show that rolling-window-based VAR models do not reveal these patterns. Regarding the directional risk transmissions, Binance was a consistent net transmitter in all three connectedness systems and it dominated the volatility connectedness network. In contrast, skewness and kurtosis connectedness networks were dominated by Litecoin and Bitcoin and Ripple were net shock receivers in all three networks. These findings are expected to serve as a guide for portfolio optimization, risk management, and policy-making practices.

This study provides evidence and proof of dynamic return connectedness alongside the revelation that certain macroeconomic factors determine the return connectedness of size-based industries of the Johannesburg Stock Exchange (JSE). The objective of this study is to examine the effect of COVID-19 on the connectedness of JSE size-based indices and to investigate the effect of macroeconomic variables on JSE size-based index connectedness under changing market conditions. By employing the time varying parameter vector autoregressive (TVP-VAR) model alongside the Diebold and Yilmaz Connectedness framework to examine the time-varying connectedness and using the Markov regime-switching model to determine the drivers of the return connectedness for the period from 4 January 2017, to 30 June 2023. The findings of this study demonstrated that the return connectedness of the JSE-size-based indices vary over time, especially in extreme market conditions such as the pre, during and post-Covid-19 periods. Moreover, the Covid-19 pandemic period reveals a season of high correlation; hence, a heightened co-movement in the returns of all JSE sized-based indices. Moreover, macroeconomic variables have an alternating effect on the connectedness of JSE sized-based indices during bull and bear market conditions. That is, the effect is regime-dependent and time varying. These findings have serious implications for portfolio diversification, in which portfolio rebalancing is needed during alternating market conditions.

This study examines the significance of foreign direct investment (FDI) and market characteristics both within and across industries in determining the productivity and efficiency of firms. This study also measures the total factor productivity (TFP) growth and its components for both foreign and domestic firms. Using Indonesian annual medium and large manufacturing establishments surveys, wholesale price index, and input-output (I-O) table, the authors calculate the horizontal and vertical spillovers and undertake stochastic frontier analysis to estimate the production and inefficiency function. The results show that the less concentrated market of domestic firms within the industry and suppliers reduces productivity and efficiency, while domestic buyers’ less concentrated markets could have the opposite effect. Most domestic and foreign firms still experience deterioration in TFP growth. The policy recommendation is to encourage firms to improve technological progress, such as upgrading machines and investing in human resources, by providing training workers aiming at mastering better managerial expertise. Policymakers should also ensure that the benefits of FDI spillovers outweigh their disadvantages.

Our estimates, based on large firm-level and industry-level data sets from eighteen countries, suggest that FDI and trade have strong positive spillover effects on product and technology innovation by domestic firms in emerging markets. The FDI effect is more pronounced for firms from advanced economies. Moreover, our results indicate that the spillover effects can be detected with micro data at the firm-level, but that using linkage variables computed from input-output tables at the industry level yields much weaker, and usually insignificant, estimated effects. These patterns are consistent with spillover effects being rather proximate and localized.

Where and when does export-led growth work? This paper estimates the importance of inter-industry productivity spillovers for the export-led growth of developing countries. My empirical strategy is based on a standard quantitative trade model that features sector-level gravity in trade flows. Applying the framework to four decades of trade data, I find clear evidence of spillovers, which are larger for skill-intensive sectors. The estimates imply that patterns of sectoral specialization play a quantitatively important role in accounting for the slow convergence of labor productivity in tradable sectors. Quantitative exercises suggest that export-led growth works for poorer countries with an initial comparative advantage in manufacturing, as these countries can use foreign demand from richer countries to reallocate labor towards sectors with high spillovers. [ABSTRACT FROM AUTHOR]

This paper proposes an imputation of a global input‐output matrix, where China is broken up into 332 prefecture‐type regions in three years of data, 2007, 2012, and 2017. Using the resulting global input‐output matrix, the paper documents that sizable spillover effects exist with regard to economic volatility. In particular, such volatility spillovers are important for prices and somewhat less so for quantity shocks. We demonstrate that individual Chinese prefectures are large recipients and donors of such shocks. All Chinese prefectures together have a very large impact on the world economy in terms of the considered volatility shocks. [ABSTRACT FROM AUTHOR]

This paper studies the volatility spillovers among commodities in both magnitude and timescale before and after the Russia-Ukraine war. We adopt the Diebold and Yilmaz (Int J Forecast 28:57–66, 2012) and the Baruník and Křehlík (J Financ Economet 16:271–296, 2018) method based the 15-min trading data. The results show that the war increases total volatility spillover from 35.54% to 49.00%. Although total spillover is the largest within a day, net spillovers of some commodities are stronger in long term. More importantly, the war increases the importance of precious metals, oil & fats, crops, and agricultural products in different time–frequency domains. The volatility spillover of precious metals as safe-haven assets within one week increases the most. The role of the oil & fats sector changes from a net receiver to a risk transmitter. Meanwhile, crops and agricultural products sectors dominate the overall spillover in the long-term during the ongoing war period. Furthermore, the time-varying results suggest that the impact of the war is durable in the long term. [ABSTRACT FROM AUTHOR]