Wage inequality and the labor market impact of economic transformation: Croatia, 1970–2008

In this paper, we examine wage inequality and wage differentials in Croatia from 1970 to 2008 using two long aggregate time series on the distribution of income. We focus especially on changing income inequality related to educational and vocational attainment, changing income inequality within those groups, and how these two components of inequality were affected by the economic transformation from socialism to capitalism. We find that income inequality between groups rose moderately post-transformation, while overall inequality increased more sharply. This finding is consistent with a growing importance of individual rather than group productivity in labor market compensation, a change broadly consistent with the economic transformation of the Croatian labor market.     

The Status of Lobbying in Croatia

The positions of lobbying and the lobbyist, well established in developed democratic societies, are far less clear in transitional countries. The aim of this paper is to present the current status of lobbying in Croatia through a discussion of its reputation in the media, citizens’ attitudes and the perceptions of business sector representatives. For that purpose, three groups of research results are presented. (1) In order to characterize the reputation of lobbying in the media, the results of a quantitative content analysis of information published in daily and weekly newspapers, magazines and on Internet portals are given. (2) To understand the attitudes of citizens to lobbying, the views of the young are considered. (3) Finally, to define perceptions of lobbying in the public sector and business, the results of a survey conducted among 50 employees in government institutions and 50 in the enterprise sector are presented and analyzed.     

Autocatalytic Growth and Development and the South-North Convergence

Abstract:

This article engages with the issue of income convergence between North and South by using the autocatalytic hypothesis of growth and development. Two system models describe positive and negative feedback loops which govern economic flows between North and South. The analysis of endogenous and exogenous negative feedbacks points to the process that would slowly push the world economy towards vanishing growth rates and, eventually, halt its material growth. The present work rejects convergence in per capita GDP between North and South from the theoretical perspective. Such an outcome would stand against one of the fundamental properties of autocatalytic dynamics—centripetality— that has its causal roots in the competitive process and capitalist institutions. In that sense, the autocatalytic hypothesis provides a theoretical explanation for those empirical analyses that dismisses convergence.     

A new non-linear AR(1) time series model having approximate beta marginals

We consider the mixed AR(1) time series model $$X_t=\left\{\begin{array}{ll}\alpha X_{t-1}+ \xi_t \quad {\rm w.p.} \qquad \frac{\alpha^p}{\alpha^p-\beta ^p},\\ \beta X_{t-1} + \xi_{t} \quad {\rm w.p.} \quad -\frac{\beta^p}{\alpha^p-\beta ^p} \end{array}\right.$$ for ?1 < β ^p ≤ 0 ≤ α ^p  < 1 and α ^p ? β ^p  > 0 when X _t has the two-parameter beta distribution B₂(p, q) with parameters q > 1 and ${p \in \mathcal P(u,v)}$ , where $$\mathcal P(u,v) = \left\{u/v : u < v,\,u,v\,{\rm odd\,positive\,integers} \right\}.$$ Special attention is given to the case p = 1. Using Laplace transform and suitable approximation procedures, we prove that the distribution of innovation sequence for p = 1 can be approximated by the uniform discrete distribution and that for ${p \in \mathcal P(u,v)}$ can be approximated by a continuous distribution. We also consider estimation issues of the model.     

Financial Support from the Family Network and Illegal Immigration

Barriers to immigration of low‐skilled workers from developing countries into the advanced countries prevent many potential migrants from leaving their countries of origin. With very low home‐country wages in relation to the cost of undocumented migration, the opportunity to migrate often hinges on the possibility of obtaining credit from a human smuggling organization or family and friends. This paper examines the conditions under which migration is optimal for an individual who lacks liquid assets, with a focus on alternative options for financing migration costs. One is by accumulating the required amount of savings out of source‐country income, with or without financial support from the family or social network. The other is debt‐bonded migration, which involves borrowing from a smuggling organization and paying off the loan while working in the host country. I find that greater financial support from the family network increases the attractiveness of debt‐bonded relative to self‐financed migration.     

Forecasting high-frequency excess stock returns via data analytics and machine learning

Borsa Istanbul introduced data analytics to present additional information about its market conditions. We examine whether this product can be utilized via various machine learning methods to predict intraday excess returns. Accordingly, these analytics provide significant prediction ratios above 50% with ideal profit ratios that can reach up to 33%. Among all the methods considered, XGBoost (logistic regression) performs better in predicting excess returns in the long-term analysis (short-term analysis). Results provide evidence for the benefits of both the analytics and the machine learning methods and raise further discussion on the semistrong market efficiency.     

Managing safety risks in helicopter maritime operations

Nowadays, helicopters have been used in maritime transportation to serve offshore platforms. This paper outlines methodology for assessing safety risks by operating in the vicinity of helidecks. During each flight, decisions must be made regarding the events that involve interactions between the four safety risk elements – the pilot in command, the aircraft, the environment and the operation. This paper evaluates helicopter crash statistics based on region and flight phase. Data collected were used for developing methodology for computing the helicopter impact frequency into facility of interest. The analysis for helicopter impact frequency calculations is based on number of operations, crash rate, frequency, average length of flight and crash area. Furthermore, the conclusion was defined based on future measurements for helicopter accidents mitigation or reduction. The presented paper contributes to safety risk assessment in helicopter maritime operations.     

Cagan’s paradox and money demand in hyperinflation: Revisited at daily frequency

Using daily data the Cagan money demand is estimated and accepted for the most severe portion of Serbia’s 1992–1993 hyperinflation, i.e. its last 6 months. An implication is that the public adjusted daily throughout this extreme period. Moreover, the obtained semi-elasticity estimates are by far lower than those previously found using monthly data sets. Consequently, the daily estimates reject the longstanding Cagan’s paradox, based on monthly studies, by showing that the economy has been on the correct, increasing side of the Laffer curve almost through the end of hyperinflation. This strongly supports the view that hyperinflation is triggered and driven all way through its end by the government’s hunt for non-decreasing seigniorage. Daily adjustments of public in hyperinflation can account for the difference between the results obtained at daily and monthly frequencies, calling into question the latter. Some evidence is offered that the findings of this paper may hold for other hyperinflations.     

Fed funds futures variance futures

We develop a novel contract design, the fed funds futures (FFF) variance futures, which reflects the expected realized basis point variance of an underlying FFF rate. The valuation of short-term FFF variance futures is completely model-independent in a general setting that includes the cases where the underlying FFF rate exhibits jumps and where the realized variance is computed by sampling the FFF rate discretely. The valuation of longer-term FFF variance futures is subject to an approximation error which we quantify and show is negligible. We also provide an illustrative example of the practical valuation and use of the FFF variance futures contract.