Econometrics

This paper investigates the relationship between the US monetary base and the five largest equity indices of the world. The mainstay of the study is the vector autoregressive approach (VAR). Analyzing impulse response functions shows strong support for the notion that the US monetary base is associated with movements in the major equity markets. For instance, positive shocks to the monetary base in the US, are responsible for positive changes in the world equity markets that may last up to six months. Examining impulse responses of equity indices from a Markov Switching VAR, which takes regime changes into account, confirm these findings. Furthermore, we show that equity responses to the positive shocks to the monetary base may be much higher than those to negative shocks. We conclude the US monetary base, and quantitative easing may have contributed to a positive business and credit climate in advanced economies of the world.

ThIS paper exammes the hypothesIs of optlmlzmg behavIOr of the U S. consumers usmg quarterly and seasonally adjusted senes on real consumer expenditures on eIght commodIty groups. clothIng, durable goods, energy, food, hOUSIng, medIcal care, transportatIon, and other~ for the perIod of 1947 I through 1993 I. FolloWIng the Weak AXIom of Revealed Preference (W ARP), a money-metnc utIlIty functIon is derIved to calculate an effIcIency mdex to determme the percentage dIfference between the obscl ved cost of consumptIon and the optImum cost of consumption m each penod of the sample The empmcal resulb provide eVidence that the allocativc effiCIency 111 the U S ha~ improved only slIghtly due to the wave of deregulatlom m the early 1980s. Our results are COTI5lstent with the predIctIOns of the general theory of second best m showmg that gams In the allocattve effiCiency may be mll1lmal a~ long as many sectors of the economy remam partially or totally regulated

Energy represents an important share of production costs for many agricultural commodities. Previous studies have found mixed evidence of a pass‐through relationship between oil prices and agricultural commodity prices, a relationship that has the potential to disrupt farm‐level decision making. We propose that these mixed findings are in part due to heterogeneity in the pass‐through relationship across time horizons. We use a new wavelet‐based regression approach to explore horizon‐based heterogeneity in the relationship between oil and agricultural commodity prices. We find strong evidence of heterogeneity across time horizons and commodities. We develop a stylized model of agricultural production and show that agricultural contracts can generate price stickiness that leads to heterogeneity in input price pass through over different horizons. We also find evidence that recent technological shifts have led to a structural change in this horizon‐based heterogeneity.

We seek to determine whether a United States President’s job approval rating is influenced by the Misery Index. This hypothesis is examined in two ways. First, we employ a nonlinear model that includes several macroeconomic variables: the current account deficit, exchange rate, unemployment, inflation, and mortgage rates. Second, we employ probit and logit regression models to calculate the probabilities of U.S. Presidents’ approval ratings to the Misery Index. The results suggest that Layton’s model does not perform well when adopted for the United States. Conversely, the probit and logit regression analysis suggests that the Misery Index significantly impacts the probability of the approval of U.S. Presidents’ performances.

This paper studies the effects of fiscal stimuli on the real GDP of the United Kingdom for the period of 1997 through the first quarter of 2017. Structural vector autoregressive and vector error correction models are estimated. Impulse responses from both models provide support for the Keynesian view that fiscal stimuli are associated with rises in the real GDP. Variance decomposition analysis shows that over time, depending which model is considered; tax cuts impart a positive effect on the real GDP in the range of 5 to 20 percent. Government expenditure shocks account for 8 to 15 percent of variations in the real GDP based on the two models. The multipliers of tax cuts and government expenditures initially rise reaching a peak in the ninth quarter and decline to 1.60 and 1.74 in three years, respectively.

This paper examines the hypothesis of optimizing behavior of the U.S. consumers using quarterly and seasonally adjusted series on real consumer expenditures on eight commodity groups: clothing, durable goods, energy, food, housing, medical care, transportation, and others for the period of 1947:I through 1993:I. Following the Weak Axiom of Revealed Preference (WARP), a money-metric utility function is derived to calculate an efficiency index to determine the percentage difference between the observed cost of consumption and the optimum cost of consumption in each period of the sample. The empirical results provide evidence that the allocative efficiency in the U.S. has improved only slightly due to the wave of deregulations in the early 1980s. Our results are consistent with the predictions of the general theory of second best in showing that gains in the allocative efficiency may be minimal as long as many sectors of the economy remain partially or totally regulated.

This paper examines the relationship between consumer confidence and consumption expenditures in the US for the period 1970:1-2007:4. Consumer confidence surveys are widely reported in the business and economics media and play an important role in the direction of business decisions and equity market movements. Despite the widely cited importance and popularity of consumer confidence indices, empirical studies attempting to establish a causal relationship between consumer confidence indices and consumption expenditures are mixed. This paper employs disaggregated consumer expenditures on services, nondurable and durable goods. The consumption functions for the three categories were obtained from the well-established Fair ( ) Macro-econometric model of the US economy. The results of our regression estimation and cointegration analysis, for both the short and long-run, suggests that consumer confidence is a determining factor for expenditures on consumer durable goods only. This finding supports the work of .

We test for the presence of low-dimensional chaotic structure in the gold and silver futures markets. While we find strong evidence of nonlinear dependencies, the evidence is not consistent with chaos. Our test results indicate that ARCH-type processes, with controls for contract-maturity effects, generally explain the nonlinearities in the data. We also make a case that employing seasonally adjusted price series is important to obtaining robust results via some of the existing tests for chaotic structure.

Employing the daily bilateral exchange rate of the dollar against the Canadian dollar, the Swiss franc and the Japanese yen, we conduct a battery of tests for the presence of low-dimension chaos.  The three stationary series are subjected to Correlation Dimension tests, BDS tests, and tests for entropy. While we find strong evidence of nonlinear dependence in the data, the evidence is not consistent with chaos.  Our test results indicate that GARCH-type processes explain the nonlinearities in the data.  We also show that employing seasonally adjusted index series enhances the robustness of results via the existing tests for chaotic structure.

This paper tests for and provides evidence of nonlinear dependencies in palladium and platinum futures prices. The results indicate that ARCH-type processes, with controls for seasonality and contract-maturity effects, generally explain the nonlinearities in the data. We also present evidence inconsistent with Chaos in the price behavior of both metals. Finally, our estimated models support the Samuelson (1965) hypothesis of

This paper examines the behavior of the US airline industry's service demand. Monthly aggregate data for the industry are analyzed. While we ®nd strong evidence of nonlinear dependence in the air transport service time series, the evidence is not consistent with chaos. We also show that GARCH models successfully explain the nonlinear structures in the US airline industry's service series. Finally, within-sample forecasts of air transport demand from the GARCH models outperform those of simple autoregressive models.

We test for the presence of low-dimensional chaotic structure in the Stock Exchange of Thailand (SET) Index. While we find strong evidence of nonlinear dependencies, the evidence is not consistent with chaos. Our test results indicate that ARCH-type processes generally explain the ...

We conduct tests for the presence of low-dimensional chaotic structure in the futures prices of four important agricultural commodities. Though there is strong evidence of non-linear dependence, the evidence suggests that there is no long-lasting chaotic structure. The dimension estimates for the commodity futures series are generally much higher than would be for low dimension chaotic series. Our test results indicate that autoregressive conditional heteroskedasticity (ARCH)-type processes, with controls for seasonality and contract-maturity effects, explain much of the non-linearity in the data. We make a case that employing seasonally adjusted price series is important in obtaining robust results via some of the existing tests for chaotic structure. Finally, maximum likelihood methodologies, that are robust to the non-linear dynamics, lend strong support to the Samuelson hypothesis of maturity effects in futures price changes.

Purpose: This study aimed to analyze cryptocurrency fundamentals against price fluctuations (case study 2019-2020). Research Methodology: The data in the research paper were accessed on the coinmarketcap.com website. The sample of this research is Bitcoin, Ethereum, Litecoin, and Bitcoin Cash. Results: The results show that: 1) Bitcoin Market Cap, Ethereum Market Cap, Litecoin Market Cap, Bitcoin Cash Market Cap have a positive and significant effect on price fluctuations. 2) Bitcoin Volume and Bitcoin Cash Volume have a positive and insignificant effect on price fluctuations. 3) Ethereum volume has a positive and significant effect on price fluctuations. 4) Litecoin volume has a negative and significant effect on price fluctuations. Limitations: Further researchers are expected to add variables such as (global macroeconomics, cryptocurrency Blockchain technology changes, psychological factors), different variables (quantitative and qualitative) and combine models to predict cryptoc...

Currently, no vaccines or specific treatments are available to treat or prevent the increasing incidence of dengue worldwide. Therefore, an accurate prediction model is needed to support the anti-dengue control strategy. The primary objective of this study is to develop the most accurate model to predict future dengue cases in the Malaysian environment. This study uses secondary data collected from the weekly reports of the Ministry of Health Malaysia (MOH) website over six years, from 2017 to 2022. Three forecasting techniques, including seasonal autoregressive integrated moving average (SARIMA), dynamic harmonic regression (DHR), and neural network autoregressive model (NNAR), were first fitted to the estimation part of the data. First, several SARIMA models were run, and the best seasonal model identified was SARIMA (0, 1, 2) (1, 1, 1)52. The best DHR model was obtained with a Fourier term of 2, as this corresponds to the lowest Akaike Information Criteria (AIC) value. The NNAR (9, 1, 6)52 was considered the best choice among the NNAR models due to its superior performance in terms of the lowest error measures. The comparison among the three techniques revealed that the DHR model was the best due to its lowest MAPE and RMSE values. Thus, the DHR model was used to generate future forecasts of weekly dengue cases in Malaysia until 2023. The results showed that the model predicted more than a thousand dengue cases around weeks 27 to 32. The results showed an increase in dengue cases after the end of the monsoon season, which lasted about five months. This technique is proving to be valuable for health administrators in improving preparedness.

This paper investigates the determinants of residential segregation using a nested logit model to disentangle household preferences for local amenities, for dwelling type and for homeownership. The model is extended to account for unobservable borrowing constraints which might prevent some households from purchasing a dwelling. A counterfactual distribution of socio-demographic characteristics across the Paris region is then built by relaxing those constraints. The comparison of the actual and counterfactual distributions suggests that if their credit constraints were alleviated, households would tend to locate further from Paris. In particular if constraints were relaxed only on the poorest households, they would not be likely to mix with the richest households.

Although the role of wine cooperatives in supporting sustainability has been deeply analysed on the supply side, the study of consumers' perception and behaviour when choosing these wines is still scarce. This paper analyses the attitudes, preferences and the willingness to pay (WTP) of European consumers, both when they purchase cooperative-produced wines and in their attitude to consuming these wines. Their preferences between cooperative-produced and organic wines were compared with the aim of understanding whether they prioritise the social aspects of the cooperatives or the environmentally friendly aspects of organic production. A survey among 3,295 individuals in different European countries was carried out. The data were firstly analysed by means of univariate tests to assess consumers' heterogeneity and by a bivariate probit model to explore the drivers of attitude and behaviour; then a multinomial logit and a random parameters logit framework were adopted. We found an association between familiarity with cooperative and organic wines and thus the propensity to buy these products and a higher WTP for organic than cooperative wines. Our findings suggest that producing organic wines might be a strategy for wine cooperatives to better target the market.

Cet article propose une étude de la plateforme ArtFacts.Net -un système de classement et de hiérarchisation des artistes de la scène mondiale de l'art contemporain -en relation aux enjeux de visibilité en ligne et de gestion des données massives dans le monde de l'art. L'étude s'appuie sur une analyse du dispositif et du discours programmatique de ce site, ainsi que sur des entretiens auprès d'informateurs-clés du monde de l'art contemporain montréalais.

The increasing deployment of renewables introduces substantial variability into the production of electricity, requiring demand to be more movable across time. We analyze data from a large Danish field experiment (2015)(2016) to investigate whether households can be prompted, via SMS messages, to move electricity consumption, and if so, whether these are motivated by pecuniary or environmental motives. The analysis has two steps: As a novel approach, we first use automatic model selection, which allows a different time-series regression for each of the 1488 households studied. From this, we obtain a cross-section of estimated SMS effects, which we then regress on the motive type. Since households can opt out there is a risk of self-selection. We therefore control for the size, income and average consumption of the household, and the age, educational-and labor market status of the SMS recipient. The results suggest that SMS messages can to some extent motivate households to move consumption. Although a stronger financial motive seems more effective, mixing financial and environmental motives seems the most effective. Finally, women and elderly people are more inclined to move consumption.

The international remittance is one of the important sources of foreign exchange earning in the country. Recently, Pakistan received over $4 billion as foreign remittances in 2006. The flows of funds through foreign remittances serve as a cushion balance of payment and foreign reserves. The paper investigated the determinants of international workers' remittances in Pakistan. The time series data was used to identify determinants of the international remittances in Pakistan. The stationary properties of each time series were investigated and each were found to be integrated of order one. Therefore, Cointegration and vector error correction models were used to establish the long run and short run relationship among the included variables in the research. The real remittances in Pakistan were found positively related with real GDP, real growth rate and unemployment rate and were negatively related with real wage rate, literacy rate and spread rate of banks in Pakistan. Based on re...

Energy traders need to decide what markets and commodities to trade in, when to open and close trades and how to maximize profits. In this paper we consider an approach for analyzing energy commodity price data based on the Levy index in order to develop a new short-term predictive trend indicator for the price. This is achieved by computing the unwrapped phase signal generated from the Levy index of both the Stochastic Volatility and price and is evaluated using data from the Irish Energy Market, namely, time series for the price of Electricity, Gas and Oil. The initial results show the predictive hypothesis holds true and algorithms are developed for implementation on an open source trading platform (Alpari MetaTrader4) which includes a range of energy commodities. This is used to demonstrate the potential of the approach in support of energy commodities trading compounded in a set of prototype MetaQuotes Language 4 (MQL4) Apps which can be downloaded and evaluated further by inte...

Discrete-choice experiments, while becoming increasingly popular, have rarely been tested for validity and reliability. This contribution purports to provide some evidence of a rather unique type. Two surveys designed to measure willingness-to-accept (WTA) for reform options in Swiss health care and health insurance are used to provide independent information with regard to two elements of reform. The issue to be addressed is whether WTA values converge although the three overlapping attributes (a more restrictive drug benefit, a delayed access to medical innovation, and a change in the monthly insurance premium) are embedded in widely differing choice sets. Experiment A contains rather radical health system reform options, while experiment B concentrates on more familiar elements such as copayment and the benefit catalogue. While mean WTA values differ between experiments, they tend to vary in similar ways, suggesting at least theoretical validity and reliability.

Salas and Raftery allege that in our paper, (1) remaining life expectancy is an endogenous explanatory variable of health care expenditure and (2) the parameter designed to correct for sample selection bias in fact represents a hidden relationship between health care expenditure and age. We argue that claim (1) is not supported by the available empirical evidence, while claim (2) seems to derive from a too cursory reading of our paper. Copyright © 2001 John Wiley & Sons, Ltd.

Originally perceived as an occasional natural hazard, drought is now a phenomena, for which one can be prepared, despite the difficulties in determining its beginning and end. It is therefore crucial to understand the individual and social behaviour, in order to adopt effective measures and policies to mitigate the negative effects of that phenomenon, reducing costs and losses.

This paper looks at bound test approach for cointegration analysis, to verify the stability of Singaporean real Gross Domestic Product (GDP), to construct the Monetary Conditions Index (MCI) over the quarterly period 1981:1-2004:4. The bounds test confirms a long-run equilibrium relationship between the output and its determinants, namely short-term and long-term interest rate, exchange rate, claims on private sector, and share prices. Results reveal evidence of cointegration between these variables in both short and long run. As such, this has further verified the stability of the Singaporean output demand function to construct the Monetary Conditions Index (MCI), and how the Monetary Authority of Singapore (MAS) responds to exchange rate changes and whether the policy responses differ. The study has evidently showed that the actual monetary stance reacts corresponding to the MCIs.

The paper aims to analyse a statistical procedure for the definition of territorial indicators, such as the biometric function of life expectancy of citizens of a territory e 0 , applying a methodology of Top-Down spatial disaggregation, using census data from 2011 in Italy. Through spatial regressions with the methodology proposed in 1971 by Chow and Lin with the use of ISTAT elaborations of annual mortality tables, which are structured from the national level to the regional level, up to the smallest details of the main level, as a dependent variable and predictors a number k of census variables plus accidents in regression models, life expectancy can also be defined at municipal levels (not elaborated by ISTAT) and even at sub-municipal levels (Census Area). The structure of the 2011 census was characterized by 152 variables, collected with CAPI and universal CAWI survey on all the survey units, throughout the national territory, divided into administrative areas of competence and 402,677 more granular areas in census sections. This structure represents a very relevant and useful information asset for applying a spatial disaggregation of indicators, based on three fundamental assumptions: 1. Structural similarity, whereby the aggregate model and the disaggregate model are structurally similar, i.e., the relationships between the variables are valid both at the aggregate (Top) and at the disaggregate (Down) level, with the consequence that the regression parameters are the same in the two models. 2. Error similarity: for spatially correlated errors they present the same structure at both aggregate (Top) and disaggregate (Down) levels, significantly testing for zero spatial correlation; 3. Reliable indicators: the variables in the regression models are efficient predictors at both aggregates (Top) and disaggregate (Down) levels, estimable from model efficiency tests. As we see in the following, compared to others, the best predictors of the census and income variables show us a good interaction in terms of active regressors on the estimation variable. Extended author information available on the last page of the article 1 Except in some years for various causes such as the war, different census lags (1936)(1937)(1938)(1939)(1940)(1941)(1942)(1943)(1944)(1945)(1946)(1947)(1948)(1949)(1950)(1951)). 2 Universal, periodic, direct, and simultaneous. 3 www. istat. it/ it/ archi vio/ 104317 Territorial Bases. 4 . europa. eu/ euros tat/ web/ nuts/ backg round 5 The United States Small-Area Life Expectancy Project (USALEEP). 6 Five homogeneous levels, plus an area writing level.

Fractional factorial designs are popularly used in different fields of experimentations, which allow experimenters to study large number of potentially relevant factors with relatively small number of experimental units but suffer from the fact that some of the effects are aliased with some others. In order to overcome these drawbacks, the foldover technique is widely used to de-alias factor effects. This article aims at using the mirror image reflection to augment a given design, to improve its properties in terms of the uniformity criterion measured by Lee discrepancy.

This paper considers R-optimal approximate designs for random coefficient regression models. An equivalence theorem for the R-optimality is provided for random coefficient regression models. Explicit expressions for R-optimal designs under linear regression models are presented for illustration.

Literature reviews reveal that the research on the issue of constructing efficient uniform designs has been very active in the last decade. In addition, coding theory is widely used in the context of constructing good optimal designs. The present paper explores the construction of highly efficient four-level uniform designs via two transformations: a modified Gray map code and a mapping between quaternary codes and the sequence of three binary codes. The efficiency is based on the viewpoint of uniformity measured by the centered L2and wrap-around L2-discrepancies of the four-level designs’ binary images. Some theoretical results related to the lower bounds of the above uniformity measures for such designs are also considered in this study. MSC: 62K15; 62K05; 62K99

Major steps 1 Framing objectives of the review 2 Identifying the relevant literature 3 Assessment of methodological quality and applicability to the clinical problem at hand 4 Summarizing the evidence qualitatively and if appropriate, quantitatively(meta-analysis) 5 Interpretation of findings and development of recommendations B.A. Dwamena (UofM-VAMC)

Integrated nested Laplace approximation (INLA) has been developed as a computationally fast, deterministic alternative to Markov chain Monte Carlo (MCMC)-based Bayesian modeling. An R interface to the C-based inla (R-INLA) program is available with extensive and diverse applications including diagnostic test accuracy meta-analysis. This talk discusses the INLA methodology briefly and in more detail illustrated application of the user-written ado-file midasinla, a deterministic bayesian version of midas, a comprehensive and medically popular module for diagnostic test accuracy meta-analysis. This Stata routine provides R-INLA estimation of the bivariate random-effects model for diagnostic accuracy meta-analysis with data pre- and post-processing within Stata. A dataset of studies evaluating axillary staging performance of positron emission tomography in breast cancer patients is provided for illustration of the omnibus capabilities of midasinla.

The umeta command performs u-statistics-based random-effects meta-analysis on a dataset of univariate, bivariate or trivariate point estimates, sampling variances, and for bivariate or trivariate data, within-study correlations or covariances. The methodology is described in ...

linear regression of log odds ratio on inverse square root of effective sample size 2 Uses the effective sample size as weight 3 Effective sample size=4*(ndis*nndis)/sample size Bivariate Mixed Effects Models 1 Focused on inferences about sensitivity and specificity but SROC curve(s) can be derived from the model parameters 2 Generalization of the commonly used DerSimonian and Laird random effects model Arends et al. Med Decis Making.

We study the statistical distribution of firm size for USA and Brazilian publicly traded firms through the Zipf plot technique. Sale size is used to measure firm size. The Brazilian firm size distribution is given by a log-normal distribution without any adjustable parameter. However, we also need to consider different parameters of log-normal distribution for the largest firms in the distribution, which are mostly foreign firms. The log-normal distribution has to be gradually truncated after a certain critical value for USA firms. Therefore, the original hypothesis of proportional effect proposed by Gibrat is valid with some modification for very large firms. We also consider the possible mechanisms behind this distribution.

This paper proposes a spatial point process model on a linear network to analyse cruise passengers’ stop activities. It identifies and models tourists’ stop intensity at the destination as a function of their main determinants. For this purpose, we consider data collected on cruise passengers through the integration of traditional questionnaire-based survey methods and GPS tracking data in two cities, namely Palermo (Italy) and Dubrovnik (Croatia). Firstly, the density-based spatial clustering of applications with noise algorithm is applied to identify stop locations from GPS tracking data. The influence of individual-related variables and itinerary-related characteristics is considered within a framework of a Gibbs point process model. The proposed model describes spatial stop intensity at the destination, accounting for the geometry of the underlying road network, individual-related variables, contextual-level information, and the spatial interaction amongst stop points. The analy...

This study examined the effect of women executives on bank risk in banks listed on the Indonesia Stock Exchange between 2017 and 2021. Women executives served as the independent variable. The dependent variable was bank risk, which is a proxy for non-performing loans and capital adequacy ratio. The financial statements of banks listed on the Indonesia Stock Exchange from 2017-2021 were used as the data source. This study used the purposive sampling method to select the sample. Panel data with the fixed effect model approach was applied in this study as the research model. According to the findings, women CEOs do not significantly affect non-performing loans and capital adequacy ratios. This is because there are no regulations requiring gender equality on company management boards, particularly in Indonesian banks, as well as challenges from social society toward women.

Globalization has led to a growing increase in financial institutions, as well as to the diversification of their services, due to the international circulation of capital. In view of this increase, the Angolan market has become progressively more competitive, making efficiency a major factor in its survival in the market. This study aimed to analyse the determinants of efficiency in the Angolan banking sector by examining the period from 2014 to 2019. To achieve this objective, we first applied the non-parametric data envelopment analysis methodology to estimate the efficiency levels of banks, and in the second phase, we used a multiple linear regression to obtain an explanatory model of Angolan banking efficiency. In the first stage, the classic Banker, Charnes and Cooper model was used with input orientation, employing the variables of staff expenses and deposits as the inputs, and the total credit as the output, ranking the banks descending order of their efficiency scores. In the second stage, through multiple linear regression, efficiency was expressed as a function of variables measuring the capital adequacy, asset quality, management quality, profitability and liquidity of the banks under study. The variables that proved to be statistically significant in the efficiency of Angolan banking were the solvency ratio, the relationship between liabilities and equity and return on equity.

Under the European Union’s Solvency II regulations, insurance firms are required to use a one-year VaR (Value at Risk) approach. This involves a one-year projection of the balance sheet and requires sufficient capital to be solvent in 99.5% of outcomes. The Solvency II Internal Model risk calibrations require annual changes in market indices/term structure/transitions for the estimation of the risk distribution for each of the Internal Model risk drivers. Transition and default risk are typically modelled using transition matrices. To model this risk requires a model of transition matrices and how these can change from year to year. In this paper, four such models have been investigated and compared to the raw data they are calibrated to. The models investigated are: A bootstrapping approach – sampling from an historical data set with replacement. The Vašíček model was calibrated using the Belkin approach. The K-means model – a new non-parametric model produced using the K-means clu...

We try to show that Discriminant Analysis can be considered as a branch of Statistical Decision Theory when viewed from a Bayesian approach. First we present the necessary measure theory results, next we briefly outline the foundations of Bayesian Inference before developing Discriminant Analysis as an application of Bayesian Estimation. Our approach renders Discriminant Analysis more flexible since it gives the possibility of classing an element as belonging to a group of populations. This possibility arises from the introduction of the concept of regions of controled posterior risk.

La presente antologia esta disenada principalmente para los alumnos de septimo semestre de la Licenciatura en Contaduria, de la Facultad de Contaduria y Administracion, de la Universidad Autonoma del Estado de Mexico, aunado a lo anterior el presente trabajo puede ser de interes para docentes, y profesionales con el deseo de adquirir nuevas competencias en el desempeno del ejercicio profesional.

The counterfactual approach provides a clear and coherent framework to think about a variety of important concepts related to causation. Meanwhile, directed acyclic graphs have been used as causal diagrams in epidemiologic research to visually summarize hypothetical relations among variables of interest, providing a clear understanding of underlying causal structures of bias and effect modification. In this study, the authors aim to further clarify the concepts of bias (confounding bias and selection bias) and effect modification in the counterfactual framework. The authors show how theoretical data frequencies can be described by using unobservable response types both in observational studies and in randomized controlled trials. By using the descriptions of data frequencies, the authors show epidemiologic measures in terms of response types, demonstrating significant distinctions between association measures and effect measures. These descriptions also demonstrate sufficient conditions to estimate effect measures in observational studies. To illustrate the ideas, the authors show how directed acyclic graphs can be extended by integrating response types and observed variables. Results: This study shows a hitherto unrecognized sufficient condition to estimate effect measures in observational studies by adjusting for confounding bias. The present findings would provide a further understanding of the assumption of conditional exchangeability, clarifying the link between the assumptions for making causal inferences in observational studies and the counterfactual approach. The extension of directed acyclic graphs using response types maintains the integrity of the original directed acyclic graphs, which allows one to understand the underlying causal structure discussed in this study. Conclusions: The present findings highlight that analytic adjustment for confounders in observational studies has consequences quite different from those of physical control in randomized controlled trials. In particular, the present findings would be of great use when demonstrating the inherent distinctions between observational studies and randomized controlled trials.

This study brings novelty to the tourism literature by re-examining the role of exchange rate in the tourism-growth nexus. It differs from previous tourism-led growth narrative to probe whether tourism exerts a positive effect on economic growth when the exchange rate is accounted for. Using a moderation modelling framework, instrumental variables general method of moments (IV-GMM) and quantile regression techniques in addition to real per capita GDP, tourism receipts and exchange rate, the study engages data on 44 Asian countries from 2010 to 2019. Results from the IV-GMM show that: (1) tourism exerts a positive effect on growth; (2) exchange rate depreciation hampers growth; (3) the interaction effect is positive but statistically not significant; and (4) results from EAP and SA samples are mixed. For the most part, constructive evidence from the quantile regression techniques reveals that the impact of tourism and exchange is significant at lower quantiles of 0.25 and 0.50 while ...

The direction of flow is not certain in which variations in the exchange rate could be transmitted to the consumer price index. To examine the transmission mechanism arising from the exchange rate to consumer price index in the Nigerian economy, eight variables-VAR model was employed in this regard. The data for the study span from the period first quarter of 2009 to the fourth quarter of 2021. The results had it that exchange rate devaluation is transmitted directly to consumer price index through a rise in the net exports and also the aggregate demand. The study therefore, recommends a rise in terms of outputs in local production so that the weight of the inflationary impact of the exchange rate devaluation could be minimal.

This paper explores the application of spatial models to non-life insurance data focused on the multi-risk home insurance branch. In the pricing modelling and rating process, spatial information should be considered by actuaries and insurance managers because frequencies and claim sizes may vary by region and the premium should be different considering this rating variable. In addition, it is relevant to examine the spatial dependence due to the fact that the frequency of claims in neighbouring regions is often expected to be more closely related than those in regions far from each other. In this paper, a comparison between spatial models, such as spatial autoregressive models (SAR), the spatial error model (SEM), and the spatial Durbin model (SDM), and a non-spatial model has been developed. The data used for this analysis are for a home insurance portfolio located in Spain, from which we have selected peril of water coverage.