nep-cis New Economics Papers
on Confederation of Independent States
Issue of 2020‒11‒23
seven papers chosen by
Alexander Harin
Modern University for the Humanities

  1. Russian Holidays Predict Troll Activity 2015-2017 By Douglas Almond; Xinming Du; Alana Vogel
  2. EU start-up calculator: impact of COVID-19 on aggregate employment: Scenario analysis for Denmark, Estonia, Finland, France, Latvia, Lithuania, Portugal and Sweden By Cristiana Benedetti Fasil; Petr Sedlacek; Vincent Sterk
  3. Can Group Identity Explain Gender Gap in Recruitment Process? By Mavlikeeva, Maria; Asanov, Igor
  4. Understanding Cross-Cultural Dfferences in Peer Reporting Practices: Evidence from Tax Evasion Games in Moldova and France By Rostan Romaniuc; Dimitri Dubois; Eugen Dimant; Adrian Lupusor; Valeriu Prohnitchi
  5. Carry trade in developing and developed countries : a Granger causality analysis with the Toda-Yamamoto approach By Bruno Tomio
  6. Parametric early warning system model for Ukraine By Shvets, Serhii
  7. Modeling and predicting foreign tourist arrivals to Sri Lanka: A comparison of three different methods By Diunugala, Hemantha Premakumara; Mombeuil, Claudel

  1. By: Douglas Almond; Xinming Du; Alana Vogel
    Abstract: While international election interference is not new, Russia is credited with “industrializing” trolling on English-language social media platforms. In October 2018, Twitter retrospectively identified 2.9 million English-language tweets as covertly written by trolls from Russia's Internet Research Agency. Most active 2015-2017, these Russian trolls generally supported the Trump campaign (Senate Intelligence Committee, 2019) and researchers have traced how this content disseminated across Twitter. Here, we take a different tack and seek exogenous drivers of Russian troll activity. We find that trolling fell 35% on Russian holidays and to a lesser extent, when temperatures were cold in St. Petersburg. More recent trolls released by Twitter do not show any systematic relationship to holidays and temperature, although substantially fewer of these that have been made public to date. Our finding for the pre-2018 interference period may furnish a natural experiment for evaluating the causal effect of Russian trolling on indirectly-affected outcomes and political behaviors — outcomes that are less traceable to troll content and potentially more important to policymakers than the direct dissemination activities previously studied. As a case in point, we describe suggestive evidence that Russian holidays impacted daily trading prices in 2016 election betting markets.
    JEL: H56 J22 J58
    Date: 2020–10
  2. By: Cristiana Benedetti Fasil (European Commission – JRC); Petr Sedlacek (University of Oxford, UK, CFM-LSE & CEPR); Vincent Sterk (University College London, UK, CFM-UCL & CEPR)
    Abstract: Early data show that the COVID-19 pandemic has affected particularly strongly start-up business activity. This may have dramatic and lasting effects on aggregate employment which persist as the cohort of new firms age. To assess such an impact, we developed the EU start-up calculator. A first application targeted to Austria, Belgium, Germany, Hungary, Italy and Spain is discussed in Benedetti Fasil, SedláÄ ek and Sterk (2020). The EU start-up calculator is an empirical tool that allows to conduct scenario analysis to compute the impact that the disruption of start-up activity has on aggregate employment on EU Member States and their economic sectors. In this paper, we simulate the effects of a strong (i.e. of magnitude equivalent to the Great Recession of 2008 and 2009) but short-lived (i.e. lasting one-year) crisis in Denmark, Estonia, Finland, France, Latvia, Lithuania, Portugal and Sweden. This shock generates important and persistent job losses in all the countries ranging between 0.9 (Portugal) and 4.5% (Latvia) from the employment trend in 2020 and results in a computed potential cumulative loss of jobs for the period 2020-2030 ranging from 59,000 (Estonia) to 798,000 (France). The potential negative impact is particularly high in Estonia, France, Latvia, Lithuania and Portugal, as well as in the service sector, which are characterized by a high firm turnover and a reliance on start-ups and young firms for job creation. We also find that in most countries the deterioration of the survival rate of young firms plays an important role in driving employment, seconded by the number of new entrants. As a consequence, policies aimed at supporting young firms and incentivizing the creation of new ones may significantly mitigate the medium-term effect of the pandemic. In fact, when we simulate bounce-back scenarios where the number of firms entering the economy rapidly increases in 2021, in every country the outlook is significantly improved, the recovery is faster and the aggregate job loss is lower.
    Keywords: COVID-19, start-ups, employment
    Date: 2020–10
  3. By: Mavlikeeva, Maria; Asanov, Igor
    Abstract: Despite evidence of the gender wage gap in favor of men, aggregate findings from correspondence studies show that women are more likely than men to be invited for a job interview (Gornall and Strebulaev, 2018). We hypothesize that the predominance of women among recruiters may explain this somewhat puzzling finding; recruiters may favor applicants of their own gender. We use the data from a large-scale correspondence study in Russia to test this hypothesis. As expected, we find that female applicants are more likely to receive callbacks for interview. We also see that in our sample the majority of contact persons responsible for the recruitment process are female. More importantly, we find that if recruiter and applicant are of the same gender, then the likelihood that the applicant will be invited for an interview increases. These findings taken together point out the gender favoritism at the hiring stage in the labor market.
    JEL: J01 J7 C93
    Date: 2020
  4. By: Rostan Romaniuc (CEREN - Centre de Recherche sur l'ENtreprise [Dijon] - BSB - Burgundy School of Business (BSB) - Ecole Supérieure de Commerce de Dijon Bourgogne (ESC)); Dimitri Dubois (CEE-M - Centre d'Economie de l'Environnement - Montpellier - FRE2010 - UM - Université de Montpellier - CNRS - Centre National de la Recherche Scientifique - Montpellier SupAgro - Institut national d’études supérieures agronomiques de Montpellier - Institut Agro - Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement); Eugen Dimant (University of Pennsylvania [Philadelphia]); Adrian Lupusor (Expert-Grup); Valeriu Prohnitchi (Expert-Grup)
    Abstract: Authorities rely on reporting from private citizens to detect and enforce more than a trivial portion of e ective law breaking. This article is the first to experimentally study the cultural aspect of peer reporting. By collecting data in a post-Soviet country (Moldova), we focus in particular on how the Soviet legacy of using citizens as private informants may have a long-lasting e ect on their willingness to cooperate with state authorities in present day; we then contrast these e ects with peer reporting behavior in a Western society (France). Our results suggest that participants in Moldova view the act of cooperating with central authorities as less socially acceptable than subjects in France and that participants in Moldova engage less frequently in peer reporting than participants in France. However, we also find that less reporting does not necessarily imply less tax compliance. Participants in both countries share very similar tax compliance rates. We explain the e ect of peer reporting on tax compliance in Moldova by the country's past experience during the Soviet era when being reported to central authorities was common and came with serious consequences for the person being denounced, ranging from shaming to expropriation.
    Abstract: U n d e r s t a n d i n g C r o s s-C u l t u r a l D f f e r e n c e s i n P e e r R e p o r t i n g P r a c t i c e s : E v i d e n c e f r o m T a x E v a s i o n G a me s i n Mo l d o v a a n d F r a n c e R u s t a m R o m a n i u c D i m i t r i D u b o i s E u g e n D i m a n t A d r i a n L u p u s o r A d r i a n L u p u s o r & V a l e r i u P r o h n i t c h i C E E-M Wo r k i n g P a p e r 2 0 2 0-1 6
    Date: 2020–11–06
  5. By: Bruno Tomio (CREG - Centre de recherche en économie de Grenoble - UGA [2020-....] - Université Grenoble Alpes [2020-....])
    Abstract: This paper explores the relationship between the carry trade and four related financial variables (interest rate differentials, market sentiment, local stock market indices, and the US stock market index) in ten currencies (Australian Dollar, Brazilian Real, Canadian Dollar, Euro, Great British Pound, Japanese Yen, Mexican Peso, New Zealand Dollar, Russian Ruble, and Swiss Franc). By considering both periods of monetary easing and tightening in the US after the 2008 crisis, I estimate Granger causality tests using the Toda and Yamamoto (1995) approach. Additionally, according to the interest rate differentials between these countries and the US, the currencies are classified as target or funding. Results show relevant differences and similarities in the long-term relationship of these variables for each analysed currency and monetary period in the US. Most importantly, regardless the strength of the US dollar (weak or strong), exchange rate is a good predictor of carry trade activity. Results for the period of monetary tightening (stronger US dollar) show that the carry trade Granger causes the market sentiment and local stock market indices. Therefore, a hawkish monetary policy in the US may be a source of systemic risk considering its effects on the carry trade.
    Keywords: carry trade,futures market,Granger causality,Toda–Yamamoto approach
    Date: 2020
  6. By: Shvets, Serhii
    Abstract: There have been several crises in the world economy since the end of the last century. The developing economies were ones that have suffered the most, considering the level of openness, the weak institutional framework, and the market vulnerability to unpredictable shocks. One of the instruments widely used to prevent crises is Early Warning System models. The paper pursues a goal to develop a parametric logit/probit regression to determine early warning arguments and their appropriate thresholds for Ukraine. The logit/probit modeling corresponds to the determination of the dependent binary variable associated with an output gap followed by the selection of independent early warning arguments. The quarterly distribution of GDP transformed into monthly data by applying the Chow-Lin regression method of interpolating higher frequency values. The monthly GDP data employed for the evaluation of the output gap using a multivariate filter and Okun’s law definition. The average elasticity of change in the unemployment rate to GDP was 3. The 2% difference between the actual and potential GDP applied for generating binary data of the output gap. There were three independent variables favored to be early warning arguments of the logit/probit regression: supply-demand gap, the world price of raw materials, and broad money supply. The obtained econometric characteristics of the probit regression were more statistically significant in comparison to the logit model. There were similar culminating positions of the fitted indicator during the crises in 2008-2009 and 2014-2015 that were different in terms of the sources. The corresponding marginal effects for the supply-demand gap, the world price of raw materials, and the broad money supply were respectively 4.0%, 0.7%, and 0.4%. Regarding the higher marginal grade, the demand-supply gap is more significant among the given early warning components for predicting crises in Ukraine. In the following study, the new arguments of the logit/probit regression have to be examined to perform higher predicting validity.
    Keywords: early warning systems, logit/probit modeling, integral composite indicators, output gap, Okun's law
    JEL: C22 C25 E27
    Date: 2019
  7. By: Diunugala, Hemantha Premakumara; Mombeuil, Claudel
    Abstract: Purpose: This study compares three different methods to predict foreign tourist arrivals (FTAs) to Sri Lanka from top-ten countries and also attempts to find the best-fitted forecasting model for each country using five model performance evaluation criteria. Methods: This study employs two different univariate-time-series approaches and one Artificial Intelligence (AI) approach to develop models that best explain the tourist arrivals to Sri Lanka from the top-ten tourist generating countries. The univariate-time series approach contains two main types of statistical models, namely Deterministic Models and Stochastic Models. Results: The results show that Winter’s exponential smoothing and ARIMA are the best methods to forecast tourist arrivals to Sri Lanka. Furthermore, the results show that the accuracy of the best forecasting model based on MAPE criteria for the models of India, China, Germany, Russia, and Australia fall between 5 to 9 percent, whereas the accuracy levels of models for the UK, France, USA, Japan, and the Maldives fall between 10 to 15 percent. Implications: The overall results of this study provide valuable insights into tourism management and policy development for Sri Lanka. Successful forecasting of FTAs for each market source provide a practical planning tool to destination decision-makers.
    Keywords: foreign tourist arrivals, winter’s exponential smoothing, ARIMA, simple recurrent neural network, Sri Lanka
    JEL: C45 C5 Z0
    Date: 2020–10–30

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