Fiscal Resilience Index - A Proposition and Evidence of Emerging Market

Fiscal resilience is essential to maintain economic stability and sustainability. Until now, there are no mutually agreed indicators to show a country's fiscal resilience. This study aims to explore the possibility of forming the index of fiscal resiliency that captures more than one underlying variable that are more comprehensive as opposed to the most current practices that use only one narrow variable. The Principal Component Analysis (PCA) method is applied to build the foundation of the index, whilst the trial is experimentally conducted as a case study of Indonesia as an emerging market in 1995-2020. Using the PCA method produces an index model of fiscal resiliency formed by the variables of government revenue, spending, debt, and macroeconomic conditions. The use of such Fiscal Resilience Index (FRI) as the case of Indonesia in the period 1995-2020 shows a reasonably consistent result which is in line with the underlying condition of the country during such period. It gives a negative figure, which means Indonesia is in a bad fiscal condition due to its budget deficit strategy.

An Association Between Phonetic Complexity of Infant Vocalizations and Parent Vowel Hyperarticulation

Extreme or exaggerated articulation of vowels, or vowel hyperarticulation, is a characteristic commonly found in infant-directed speech (IDS). High degrees of vowel hyperarticulation in parent IDS has been tied to better speech sound category development and bigger vocabulary size in infants. In the present study, the relationship between vowel hyperarticulation in Swedish IDS to 12-month-old and phonetic complexity of infant vocalizations is investigated. Articulatory adaptation toward hyperarticulation is quantified as difference in vowel space area between IDS and adult-directed speech (ADS). Phonetic complexity is estimated using the Word Complexity Measure for Swedish (WCM-SE). The results show that vowels in IDS was more hyperarticulated than vowels in ADS, and that parents’ articulatory adaptation in terms of hyperarticulation correlates with phonetic complexity of infant vocalizations. This can be explained either by the parents’ articulatory behavior impacting the infants’ vocalization behavior, the infants’ social and communicative cues eliciting hyperarticulation in the parents’ speech, or the two variables being impacted by a third, underlying variable such as parents’ general communicative adaptiveness.

A SARIMA and Adjusted SARIMA Models in a Seasonal Nonstationary Time Series; Evidence of Enugu Monthly Rainfall

The paper compares SARIMA and adjusted SARIMA(ASARIMA) in a regular stationary series where the underlying variable is seasonally nonstationary. Adopting empirical rainfall data and Box-Jenkins iterative algorithm that calculates least squares estimates, Out of 11 sub-classes of SARIMA and 7 sub-classes of ASARIMA models, AIC chose ASARIMA(2,1,1)12 over all sub-classes of SARIMA(p,0,q)x(P,1,Q)12 identified. Diagnostic test indicates absence of autocorrelation up to the 48th lag. The forecast values generated by the fitted model are closely related to the actual values. Hence, ASARIMA can be recommended for regular stationary time series with seasonal characteristics and where parameter redundancy and large sum of square errors are penalized.

New insight into market concentration and competition: Use of Barnett’s variable profit function to measure market structure in banking

Previous research on market concentration in banking is heavily tilted towards using deposits as the underlying variable for measuring market concentration. This paper proposes a change in methodology by replacing deposits with the Variable profit function based on Barnett and Hahm’s Economic model for Financial Institutions, used in their 1994 paper. This model has also been successfully used in Dr. William A. Barnett’s successive research. Hancock 1997 also proposes using a similar methodology for modelling banks as Economic firms. Results change dramatically once deposits are substituted by variable profits, and a confounding puzzle is solved, involving one of South Asia’s thriving banking markets.

Angular similarity in test parameters

Through N-dimensional person space, the article gives measures of test parameters and item statistics, including difficulty/discriminating value of test, correlations between a pair of items, and item-total correlations with binary items using angular similarity between two vectors. Relationships between difficulty value and discriminating value of items and test were derived, including relationship between test reliability and test discriminating value. Reliability of a test as per theoretical definition in terms of length of score vectors of two parallel subtests and angle between such vectors was derived. The method was extended to find reliability of a battery of tests. Reliability and discriminating value of a Likert-type item and scale was found in terms of angular similarity without involving assumptions of continuous nature or linearity or normality for the observed variables, or the underlying variable being measured. The proposed methods also avoid test of unidimensionality or assumption of normality or bivariate normality associated with the polychoric correlations. Thus, the proposed methods are in fact nonparametric and considered as improvement over the existing ones. Reliability as a measure of association of two vectors and discrimination as a measure of distance between the vectors are likely to show a negative relationship.

Logistics Performance Index: Methodological Issues

This article addresses limitations of Logistics Performance Index (LPI) and suggests remedies. Reliability of the instrument used in LPI may be better found by Angular Association method or Bhattacharyya’s measure, using only the frequencies or probabilities of item–response categories without involving assumptions of continuous nature or linearity or normality for the observed variables or the underlying variable being measured. The suggested methods also avoid test of uni-dimensionality, assumption of normality, bivariate normality. The problems of outlying observations and linear assumptions in principal component analysis for finding reliability theta are also avoided in each proposed method. Geometric mean approach provides a better alternative to compute LPI scores avoiding scaling and calculation of weights satisfies many desired properties and reduces level of substitutability between components, facilitates statistical test of equality of two geometric means and identifies critical areas for corrective measures. Such identifications are important from a policy point of view. The graph of LPI for a country over a long period of time reflects pattern of growth of LPI for the country. The method helps to rank and benchmark the countries, if the target vector is taken as LPI score of the best performing country. JEL Codes: C43, C54

Are benefit reductions an effective activation strategy? The case of the lowest benefit recipients in Denmark

Decades of commitment to the basic principles of the Danish welfare state have been discarded with a new social policy reducing the benefits for people already at the bottom of the income ladder. The political intention is to increase job search via economic incentives that increase the gap between benefit income and market income. Using a panel dataset with benefit recipients, we show that the intended job search effect did not materialise to any significant extent; rather, the affected people became poorer because the vast majority of individuals could not respond to the economic incentives in the intended manner. Joblessness was not due to lack of incentives. This study confirms the importance of employability and self-efficacy, but it shows that health is an underlying variable that explains both of these factors and the recipients’ difficulties in getting a job. The results have two major social policy implications. Access to early retirement schemes should be easier for recipients who have serious health problems and therefore cannot respond to economic incentives, and there should be an increased focus on how to help the recipients without major health problems to develop self-efficacy.

Two processes are not necessary to understand memory deficits

Bastin et al. propose a dual-process model to understand memory deficits. However, results from state-trace analysis have suggested a single underlying variable in behavioral and neural data. We advocate the usage of unidimensional models that are supported by data and have been successful in understanding memory deficits and in linking to neural data.

Using Partial Credit Model to Improve the Quality of an Instrument

<p>In using the Rasch model to improve the quality of an instrument, analysis purports to determine if the sample collaborates well with the items in the instrument such that the results are measuring a single underlying variable. The relevant properties of Rasch analysis are reliability and validity which are key indicators of the quality of a measurement instrument. This paper discusses the use of one type of Rasch model that is the Partial Credit Model to investigate reliability and validity of an instrument. By removing or changing items in the instrument when conditions of reliability and validity are not met, the quality of the instrument is improved.</p>