Factors Driving Quality Standard Compliance in the Polish Dairy Sector

We construct a model to identify determinants of the diffusion rate of quality standards in a food chain. We argue that adoption decisions in the food chain are determined by farmers’ and processors’ economic considerations. Factors such as pricing behaviour, compliance costs and market structure are identified and discussed in the paper. The findings are used to test an econometric model utilizing data on Polish milk processing firms gathered between 2000 and 2002. The results indicate that input and output prices have a significant influence on the diffusion rate of standards; the dominance of large-scale holdings in the relevant procurement market significantly increases diffusion as well. Compared to their competitors, small cooperatives were found to face more significant problems in procuring high quality raw materials.      

Unit Root Analyses of the Causality Between Japanese Money and Income

Unit root techniques and cointegration analysis have develop ed considerably in the last ten years. At the same time, the nonstationary test for Granger causality has been developed. We shed some new light on Japanese money supply and income causality by using nonstationary techniques. We specify univariate ARMA models of money, income, GNP deflator and rate of interest, initially by using the Dickey and Fuller (DF) or the augmented DF (ADF) tests. Two diagnostic tests are applied to each selected ARMA regression. One is the residual DF test, and the other is the moving average (MA) unit root test of residuals . After selecting the ARMA model, some causality tests are applied to the error correction model (ECM) of a vector autoregression (VAR) one of which is ordinary least squares (OLS) and another is the maximum likelihood (ML) method. The former requires only the standard F -test on the deleted variables in the ECM. The latter requires the Johansen's ML method in estimating cointegration. Causality is found to go from income to money supply but not the other way. Appendices include a simple implementation of the MA unit root test, a pedagogical proof of the Granger causality tests developed by Toda and Phillips (1993) and an interpretation of the test proposed by Toda and Yamamoto (1995).
JEL Classification Numbers: C32, E50     

A Modified GARCH Model with Spells of Shocks

The GARCH model is modified to capture the effect on volatilities of the consecutive number of positive or negative shocks. The new model is tested against the Shanghai Shcomp and Nikkei225 indices and found particularly useful in analyzing the Shcomp index. Similarly, the EGARCH model is extended along the same line as the GARCH model and is applied to the same sets of data. Stationarity of the new GARCH (1, 1) model is proved, and also derived is the asymptotic distribution of the quasi-maximum likelihood estimator.     

Asymptotic expansions of the distributions of the estimates of coefficients in a simultaneous equation system

In this paper asymptotic expansions are derived for the density functions of the TSLS and LIML estimates of coefficients in a simultaneous equation system when the sample size increases and the effect of the exogenous variables increases along the sample size. These approximations are used to compare the asymptotic moments of the TSLS and LIML estimates and the concentration of probability around the true value of the estimates.     

Network analysis approach to map tourism mobility

The spatial distribution of tourists is uneven and it can include some areas at regional and/or sub-regional level. The social–economic and environmental impacts of tourism, are concentrated in different areas. Some recent contributions show the usefulness and the effectiveness of network analysis (NA) approach in revising the organization of tourist facilities and services. This paper proposes to apply methods borrowed from NA to map the spatial distribution of tourism mobility in Sicily. So, we analyze the network features of tourism in a multi-destinations net. By means of traditional measures of NA, we propose to measure the links among destinations. The study aims to connect destinations, represented as nodes, to define a territorial network of tourism demand. In the specific instance, the degree centrality, closeness centrality, betweenness centrality are used to localize central areas and the main routes. We test survey data collected on a sample of tourists leaving from airports and ports of the main Sicilian cities, who visited two destinations at least. Then, we study tourism mobility on those areas selected by tourists. Finally, employing measures derived from NA, the work attempts to set out territorial networks. This approach could be useful to plane tourism development policies.     

Mapping AcroQoL scores to EQ-5D to obtain utility values for patients with acromegaly

Aims: To estimate a preference-based single index for the disease-specific instrument (AcroQoL) by mapping it onto the EQ-5D to assist in future economic evaluations.

Materials and methods: A sample of 245 acromegaly patients with AcroQoL and EQ-5D scores was obtained from three previously published European studies. The sample was split into two: one sub-sample to construct the model (algorithm construction sample, n?=?184), and the other one to confirm it (validation sample, n?=?61). Various multiple regression models including two-part model, tobit model, and generalized additive models were tested and/or evaluated for predictive ability, consistency of estimated coefficients, normality of prediction errors, and simplicity.

Results: Across these studies, mean age was 50–60 years and the proportion of males was 36–59%. At overall level the percentage of patients with controlled disease was 37.4%. Mean (SD) scores for AcroQoL Global Score and EQ-5D utility were 62.3 (18.5) and 0.71 (0.28), respectively. The best model for predicting EQ-5D was a generalized regression model that included the Physical Dimension summary score and categories from questions 9 and 14 as independent variables (Adj. R²?=?0.56, with mean absolute error of 0.0128 in the confirmatory sample). Observed and predicted utilities were strongly correlated (Spearman r?=?0.73, p?<?.001) and paired t-Student test revealed non-significant differences between means (p?>?.05). Estimated utility scores showed a minimum error of ≤10% in 45% of patients; however, error increased in patients with an observed utility score under 0.2. The model’s predictive ability was confirmed in the validation cohort.

Limitations and conclusions: A mapping algorithm was developed for mapping of AcroQoL to EQ-5D, using patient level data from three previously published studies, and including validation in the confirmatory sub-sample. Mean (SD) utilities index in this study population was estimated as 0.71 (0.28). Additional research may be needed to test this mapping algorithm in other acromegaly populations.     

Decision rules for the choice of structural equations

In practical econometric analysis we are faced with the problem of how to specify structural equations. The conventional t-test of coefficients is apparently inappropriate. The smallest root, say λ, of a certain determinantal equation provides us with basis for the test of overidentifying restrictions. The preliminary test, based on λ, may give us a possible decision rule for choosing a structural equation from nested alternatives. However, ambiguity remains in specifying the significance level. We propose a decision method called the unbiased decision rule; unbiased in the sense that we attain a correct decision with probability of more than a half. The critical points are found as the medians of non-central F-distributions. The degrees of freedom and the non-centrality parameter of non-central F-distributions are determined by the properties of contending models. We also discuss the implications of the unbiased decision rule in the context of the conventional pre-test.     

The leverage effect puzzle: the case of European sovereign credit default swap market

One of the stylized facts about the behaviour of time series is that their volatility exhibits asymmetrical responses to good and bad news. In the case of stock markets, volatility seems to rise when the stock price decreases and fall when the stock price increases. This so-called “leverage effect” was first described by Black (Proceedings of the 1976 meeting of the business and economic statistics section, pp 177–181, 1976). The concept is not new and has already been comprehensively studied and implemented in many volatility models (GARCH and SV) in the form of an additional parameter in the volatility equation. However, there is no study or a theoretical explanation of the leverage effect in sovereign credit default swap spreads (hereinafter: sCDS). In this article, we discuss the possible behaviour of sCDS volatility and explain it by way of reference to the Prospect Theory by Kahneman and Tversky (Econometrica 47(2):263–292, 1979). We estimate a series of stochastic volatility models with the leverage effect, proposed by Yu (J Econom 127(2):165–178, 2005). In this model, the “leverage effect” is, in fact, the same as a coefficient of the correlation between the current return of an asset and its expected future volatility. We show that the effect does exist and differs across markets. As far as the safe European markets are concerned, the parameter is negative; in the case of extremely risky economies—it is positive. In markets of medium risk the effect varies depending on the relationship between the perceived risk and the value of the sCDS premium.     

Institutional Analysis of Banks and Personal Loan Companies: Lesson from Poland

Abstract:

The purpose of the article is to explain changes in the behavior of individuals, their actions, choices and ways of thinking that took place under the influence of banking and personal loan companies in Poland. The hypothesis adopted here is that mistakes made in the lawmaking process in Poland caused a number of adverse social changes, which affected the poorest part of society. The article is devoted to legal norms which banks started to apply as prudential regulations after the financial crisis from 2008 to 2015. In 2016, new important legal regulations were introduced which slightly changed the image of the market described in the article. The article describes the results of the author’s research concerning far-reaching social consequences of the regulations introduced at that time. Such consequences include people already in the lowest-income levels of society falling further into poverty, as well as loss of trust in the state as an institution failing to protect all of its citizens.