On the Estimation of Cross-Firm Productivity Spillovers with an Application to FDI

We develop a novel methodology for the proxy variable identification of firm productivity in the presence of productivity-modifying learning and spillovers which facilitates a unified "internally consistent" analysis of the spillover effects between firms. Contrary to the popular two-step empirical approach, ours does not postulate contradictory assumptions about firmproductivity across the estimation steps. Instead, we explicitly accommodate crosssectional dependence in productivity induced by spillovers which facilitates identification of both the productivity and spillover effects therein simultaneously. We apply our model to study cross-firm spillovers in China's electric machinery manufacturing, with a particular focus on productivity effects of inbound FDI.

An Approach to Measure the Performance and the Efficiency of Future Airport Infrastructure

The aim of this paper is to design an approach to evaluate the expected efficiency and performance of future airport infrastructure. First, an airport sampling method to select similar airports is developed based on socioeconomic and operational airport variables that are summarized in a proxy variable; second, the ARIMA-GARCH-Bootstrap method is applied to forecast the selected outputs (PAX and ATMS) whilst the selected inputs (Cities, Gates, Runaways, Airport Size, Pax carriers, and Num. of employees) remain constant; and third, the VRS-OO and the CRS-OO DEA models are implemented to evaluate the efficiency and performance of the airports in the current and future years. The proposed approach is used to evaluate the future airport infrastructure of the new Mexico City Airport against 19 representative worldwide airport hubs. The proposed approach is applied to analyze the Mexico City Airport multi-airport system infrastructure as a case study. The results show that this multi-airport system requires more airside infrastructure that must be added by the new Mexico City Airport, airlines should operate aircrafts with more capacity to serve more PAX per ATM, and airlines must open new connections at the new Mexico City Airport to increase the expected efficiency and performance of this multi-airport system.

Burnout during the COVID pandemic: a case of the social services sector in Latvia

The paper analyses the results of an online survey of 443 social services sector employees carried out in October and November 2020 in Latvia. The survey was aimed to measure the impact of the pandemic on the social services sector, i.e. how social services were delivered, whether restrictions imposed have any effect on a given service (form, quality, quantity) as well as how social services sector organizations and employees coped with the pandemic both at organizational and psychological levels. A short version of the burnout measure developed by Ayala Malach-Pines was used to estimate the burnout level among social services sector employees. The survey results indicate that about one third of the surveyed employees are exposed to a high risk of burnout. Contrary to other studies, burnout has no relationship with the number of clients (a proxy variable for workload) served in a given institution. Burnout is more likely associated with factors related to the methodological, technical support and overall working conditions in one’s organization.

THE REGIME SWITCHING OF CYCLE INSTABILITY OF ISLAMIC BANKING AND THE ECONOMY: EVIDENCE FROM INDONESIA, MALAYSIA, AND PAKISTAN

This study aims to examine the cyclical instability of Islamic banking in Indonesia, Malaysia, and Pakistan. A stable Islamic banking system can give the public confidence to conduct transactions and thus grow the economy. The proxy variable for stability used is the z-score, with 156 periods of research data from January 2007 to December 2019. The Markov Switching Vector Autoregression (MS-VAR) method was employed. The results show that Islamic banking stability in Indonesia based on the z-score is more stable than others. Nevertheless, in terms of the regression of all the variables, regime shifting, and the duration of the crisis, overall Malaysian Islamic banking displays the best performance. The instability of the Indonesian model is mostly affected by inflation, whereas Malaysia and Pakistan are affected by the financing to deposit ratio and the fluctuation in global oil, respectively.

Finding Myself Fast and Furiously: The Role of Agency-Communion Orientation and Self-Concept Clarity in Support for Radicalism

The past research on radicalism is equivocal regarding the ways in which self-concept clarity shapes intentions to engage in radical behavior. Seeking to address the previous mixed findings in the literature, the present research examines how an individual’s agency-communion orientation moderates the effect of self-concept clarity on behavioral intentions for radical groups. Specifically, we propose that agency-oriented individuals show greater intentions to participate in radical groups when they experience low (vs. high) self-concept clarity, whereas communion-oriented individuals show no significant differences in their intentions to participate in radical groups across levels of self-concept clarity. A 2 (agency-communion orientation: low vs. high) × 2 (self-concept clarity: low vs. high) experimental design was used to test the hypotheses. Using gender as a proxy variable for agency-communion orientation, Study 1 shows that agency-communion orientation moderates the effect of self-concept clarity on intentions to participate in radical groups. Using chronic individual differences in agency-communion orientation, Study 2 shows that psychological entitlement mediates the interactive effect of self-concept clarity and agency-communion orientation on behavioral intentions for radical groups. Taken together, these findings support the role of agency-communion orientation and self-concept clarity in radicalism.

Modelling Volatile Time Series with V-Transforms and Copulas

An approach to the modelling of volatile time series using a class of uniformity-preserving transforms for uniform random variables is proposed. V-transforms describe the relationship between quantiles of the stationary distribution of the time series and quantiles of the distribution of a predictable volatility proxy variable. They can be represented as copulas and permit the formulation and estimation of models that combine arbitrary marginal distributions with copula processes for the dynamics of the volatility proxy. The idea is illustrated using a Gaussian ARMA copula process and the resulting model is shown to replicate many of the stylized facts of financial return series and to facilitate the calculation of marginal and conditional characteristics of the model including quantile measures of risk. Estimation is carried out by adapting the exact maximum likelihood approach to the estimation of ARMA processes, and the model is shown to be competitive with standard GARCH in an empirical application to Bitcoin return data.

Overt or covert? Effect of different digital nudging on consumers’ customization choices

Purpose This study aims to explore the effect of two digital nudging technologies that is overt digital nudging (ODN) and covert digital nudging (CDN), on consumers’ choices of nudged options in the context of online customization systems (OCS). Design/methodology/approach This paper designed a 2 (ODN: yes/no) by 2 (CDN: yes/no) full factor between-subject lab experiment in the context of online travel package customization. This paper collected and analyzed the number of nudged options (the intermediate options) of choices among consumers in these four scenarios. Findings ODN and CDN have positive effects on consumers’ choices of nudged options in online customization (OC). In addition, mixed nudge (a combination of ODN and CDN) has a more significant effect on consumers’ choices of nudged options in OC than using CDN only. Research limitations/implications This study focused only on the choice behavior of consumers in the customization context and did not analyze their attitude change. The present study used vendor recommendation as the proxy variable of ODN and default option as the proxy variable of CDN. A future study could explore other instances of ODN and CDN. Practical implications This study explores the effects of digital nudging technologies in the context of OCS. The study provides clear guidance for customization vendors on whether to use digital nudging tools and their combinations, and which tools should be preferred. Social implications Vendors can adopt digital nudging technology to persuade consumers to choose nudged options. This nudging effect can make consumers’ choices predictable and less uncertain, thus adding profits for vendors. Originality/value First, the study focuses on the impact of digital nudging on consumers’ choices and enriches the understanding of the impact of customization system design on consumers’ choices. Second, this paper put forward a new classification method for digital nudging and proposed, respectively, the effect mechanisms on consumers’ customization choices. Third, this study explores the effect of combining multiple nudging tools in OC context on consumers’ choices, which deepens the understanding of the interactive effects of different types of nudging tools.

Evacuation Departure Timing during Hurricane Matthew

This study investigates evacuation behaviors associated with Hurricane Matthew in October of 2016. It assesses factors influencing evacuation decisions and evacuation departure times for Florida, Georgia, and South Carolina from an online survey of respondents. Approximately 62% of the Florida sample, 77% of the Georgia sample, and 67% of the South Carolina sample evacuated. Logistic regression analysis of the departures in the overall time period identified variability in evacuation timing, primarily dependent on prior experience, receipt of an evacuation order, and talking with others about the evacuation order. However, using four logistic regressions to analyze differences in departure times by day shows that the only significant variable across the three main days of evacuation was our proxy variable for evacuation-order times. Depending on the day, other variables of interest include number of household vehicles, previous hurricane experience, and receipt of an evacuation order. Descriptive results show that many variables are considered in the decision to evacuate, but results from subsequent analyses, and respondents’ comments about their experiences, highlight that evacuation orders are the primary triggering variable for when residents left.