Proposed model for predicting economic growth based on the Keynesian aggregate demand equation: Case of Ecuador 1965-2018

It is important for researchers and economic policy makers to forecast GDP but sometimes it is complicated or expensive to access the information of the five components of the equation, so this research proposed to validate a model as parsimonious as possible that would make reliable predictions of GDP. Through an iterative process they were estimated and validated, using multiple linear regression and based on the Expenditure Method equation, equations to whichnon-significant and / or less explanatory regressors were eliminated seeking maximum parsimony, to then prove the predictive power of valid equations. As a result, a statistically valid estimator with high predictive power was found, but it includes the five regressors of the original equation. Keywords: GDP, aggregate demand, forecast, parsimony. References [1]E. López Fernández de Lascoiti, «CRACK DE 1929: Causas, desarrollo y consecuencias.,» Revista Internacional del Mundo Económico y del Derecho, vol. I, pp. 1 - 16, 2009. [2]J. Montano, «Gran Depresión: Causas, Características y Consecuencias,» 2019. [Online]. Available: https://www.lifeder.com/gran-depresion/. [3]M. Rapoport, «La crisis de 1929, la teoría económica y el New Deal,» 2008. [Online]. Available: https://www.pagina12.com.ar/diario/economia/subnotas/111712-35315-2008-09-17.html. [4]J. Ros, «La Teoría General de Keynes y la macroeconomía moderna,» 2012. [Online]. Available: https://www.redalyc.org/pdf/601/60123307002.pdf. [5]M. Kiziryan, «Demanda agregada,» 2019. [Online]. Available: https://economipedia.com/definiciones/demanda-agregada.html. [6]G. Mankiw, Macroeconomía, 6ta. Ed., España: Antoni Bosch, editor, S.A., 2006. [7]L. Gastón Lorente, «Cómo calcular el PIB: Tres métodos,» 2019. [Online]. Available: https://www.bbva.com/es/bbva-patrocina-el-almuerzo-inaugural-de-la-cumbre-del-clima-disenado-por-los-hermanos-roca/. [8]R. Dornbusch, S. Fischer and R. Startz, Macroeconomía, 10ma. Ed., México D. F.: McGraw-Hill/Interamericana Editores, S.A. de C.V., 2009. [9]A. B. Abel and B. S. Bernanke, Macroeconomía, 4ta. Ed., Madrid: Pearson Educación S.A., 2004. [10]S. Jahan, A. Saber Mahmud and C. Papageorgiou, «¿Qué es la economía keynesiana?,» 09 2014. [Online]. Available: https://www.imf.org/external/pubs/ft/fandd/spa/2014/09/pdf/basics.pdf. [11]D. A. Lind, W. G. Marchal and S. A. Wathen, Estadística aplicada a los negocios y la economía. 15ta. Ed., México D.F.: McGraw Hill/Interamericana Editores S.A. de C.V., 2012. [12]R. S. Pindick and D. L. Rubinfeld, Econometría: Modelos y pronósticos, 4ta. Ed., México D.F.: McGraw-Hill Interamericana, 2001. [13]D. R. Anderson, D. J. Sweeney and T. A. Williams, Estadística para administración y economía. 10ma. Ed., México D.F.: Cengage Learning Editores, S.A., 2008. [14]Banco Central del Ecuador, «Información Económica-Estadísticas del sector real,» 2020. [Online]. Available: https://contenido.bce.fin.ec/documentos/Administracion/CuentasNacionalesAnuales.html. [15]D. N. Gujarati and D. C. Porter, Econometría. 5ta. Ed., México, D. F.: McGraw Hill Educación, 2010. [16]E. Court and E. Williams, Estadísticas y econometría financiera, 1ra. Ed., Buenos Aires: Cengage Learning Argentina, 2011. [17]R. Montero Granados, «Modelos de regresión lineal múltiple,» Documentos de Trabajo en Economía Aplicada. Universidad de Granada. España, 2016. [18]R. A. Fernández Montt, «Regresión lineal. Multicolinealidad perfecta,» 2006. [Online]. Available: http://www.eumed.net/cursecon/medir/rfm-multico.htm. [19]C. . H. Achen, Interpreting and Using Regression, Beverly Hills: Sage, 1982. [20]J. M. Wooldridge, Introducción a la econometría. Un enfoque moderno. 4ta. Ed., México, D. F.: Cengage Learning, 2010. [21]R. Geary, «Some Results about Relations Between Stochastic Variables: A Discussion Document,» Review of International Statistical Institute, vol. 31, pp. 163-181, 1963.

Alteration of Consumption Habits in Turkey Over Time

Simon Kuznets and John Maynard Keynes did research on the subject of propensity to consume. Kuznets asserted that people do not alter their consumption/saving ratio and spend more when they have more disposable income. Keynes alleged that when disposable income increases, the rate of saving also increases over time because people tend to keep their consumption habits steady. Namely, the consumption/saving ratio of households or individuals tends to decrease as disposable income goes up. And in this study, the Keynesian consumption function is investigated in the Turkish economy. The result of this research might give insight into the future of the consumption/saving ratio in Turkey. In the study, the ARDL econometric model is operated with data from the Turkish Statistical Institute. The result of the study is that people change their consumption habits with the increase of disposable income. As a result, the consumption level has been slowing down, and the propensity to consume diminishes. That proves that the Keynesian consumption function holds in Turkey.

Before, During, and After the First Wave of COVID-19: Mortality Analyses Reveal Relevant Trends in Germany and its States until June 2020

ABSTRACT Objective Well-established mortality ratio methodology can contribute to a fuller picture of the SARS-CoV-2/COVID-19 burden of disease by revealing trends and informing mitigation strategies. This work examines respective data from Germany by way of example. Methods Using monthly and weekly all-cause mortality data from January 2016 to June 2020 (published by the German Federal Statistical Institute) for all ages,<65 years and≥65 years, and specified for Germany’s federal states, we explored mortality as sequela of COVID-19. We analysed standardized mortality ratios (SMRs) comparing 2020 with 2016–2019 as reference years with a focus on trend detection. Results In Germany as a whole, elevated mortality in April (most pronounced for Bavaria) declined in May. The states of Hamburg and Bremen had increased SMRs in all months under study. In Mecklenburg-Western Pomerania, decreased SMRs in January turned monotonically to increased SMRs by June. Irrespective of age group, this trend was pronounced and significant. Conclusions Increased SMRs in Hamburg and Bremen must be interpreted with caution because of potential upward distortions due to a “catchment bias”. A pronounced excess mortality in April across Germany was confirmed and a hitherto undetected trend of increasing SMRs for Mecklenburg-Western Pomerania was revealed. To meet the pandemic challenge and to benefit from research based on data collected in standardized ways, national authorities should regularly conduct SMR analyses. For independent analyses, national authorities should also expedite publishing raw mortality and population data, including detailed information on age, sex, and cause of death, in the public domain.

Determinants of online shopping attitudes of households in Turkey

Purpose Online shopping is expected to continue without slowing down because of the advantages that it presents to consumers in the digitalising world. This study aims to determine the factors regarding the social and environmental indicators and the demographical and economical factors that affect the online shopping tendencies of households in Turkey. The results of this research can be used to review the online shopping strategies by the decision-makers. Design/methodology/approach In this study, the cross-sectional data acquired from the Household Budget Research survey, which has been conducted by the Turkish Statistical Institute between 2015 and 2018, is used. In this data set consisting of 11,491 in 2015, 12,096 in 2016, 12,166 in 2017 and 11,828 in 2018, a total of 47,581 data from the households that are 15-year-old and older are used. To determine the factors affecting the online shopping behaviour of households, binary logistic regression and binary probit regression analyses are applied. As a result of these analyses, it has been decided that the most suitable model is the binary probit regression model. Findings According to the analysis results, it has been detected that factors such as educational status, age, marital status, employment status, income, life assurance ownership, credit card usage, automobile ownership and the year of the survey affect the online shopping behaviour of households. Practical implications In this study, factors affecting the tendency to do online shopping, which has gained big importance particularly with the COVID-19 pandemic, are determined. In Turkey, households’ tendency to do online shopping is affected by the demographical and economical factors and by the factors related to the social and environmental indicators. Determination of the effects of these factors has been a guide for the decision-makers and policymakers in explaining the tendency to shop online and creating a competitive advantage. Originality/value In this study, data consisting of a total of 47,581 observations, which has acquired from the Household Budget Research survey conducted by the Turkish Statistical Institute between 2015 and 2018, are used by applying a weighting process, and no study that is as comprehensive and inclusive as this study has been found in the literature, e-commerce that has become prevalent with the help of technological progress and changing habits in the past years is continuing to become prevalent more increasingly particularly after COVID-19 pandemic. Therefore, the value of this study underlies its contribution to e-commerce awareness.

Fostering Statistical Literacy in Greece

The Hellenic Statistical Authority (ELSTAT), the National Statistical Institute of Greece, as the guarantor of the quality of official statistics in Greece, has been pursuing, since 2016, an ambitious strategy aiming to foster Statistical Literacy, focusing on strengthening ties with citizens in their dual capacity both as providers of data and ultimately as users of statistics, and thus, operate as crucial enablers of a smoothly functioning virtuous circle of official statistics. Objectives include the development of an understanding of basic methodologies and tools used in official statistics, along with the awareness of its institutional foundations and core principles. This critically contributes to the value of official statistics being spread and effectively communicated, making, at the same time, a convincing case for fact-based decision making in the daily lives of the main stakeholders. This article motivates the approach followed in developing a specific strategy on statistical literacy, outlines its philosophy and main objectives and browses through the array of initiatives and actions undertaken over the last five years. In addition, it explores the responsiveness of citizens to these initiatives and the extent to which these initiatives lead to an increased engagement of key targeted stakeholders.

Suicide Cause and Method from 2009-2017 in Turkey

Background: This study was planned to investigate the cause, method, age group and gender of suicides between 2009 and 2017 in Turkey. Methods: Data on suicide deaths between the years 2009-2017 were obtained from the death data of the Turkish Statistical Institute. Results: Suicide data were evaluated according to age group, gender, reason and method. The most common suicide methods among people living in Turkey were hanging oneself, using a firearm and throwing oneself from a high place whereas common causes and unknown causes were found to be illness and economic problems. Gender showed statistical significance in the cause of suicide in all suicide methods (illness, economic problems, job failure). According to age groups the reasons were family disharmony, emotional relationship and not being able to marry the desired person, Education failure were found to be statistically significant. Less used methods to commit suicide in Turkey were determined as using firearms, using natural gas or LPG, throwing from a train or motor vehicle. Conclusion: It is a very sad situation for an individual to end his/her life conspiratorially. Appropriately collected suicide information can guide the design of suicide prevention strategies. Because previous suicide attempts seem to be an important risk factor for future attempts and death by suicide.

Socio-demographic determinants of happiness in Turkey

This study examines the relationship between the perception of happiness and socio-demographic characteristics in Turkey using the Life Satisfaction Survey conducted by the Turkish Statistical Institute in 2017. For this purpose, nonlinear canonical correlation analysis was performed on a dataset of 4261 employees. Socio-demographic characteristics evaluated the variable set consisting of both the individual's direct perception happiness and the conceptual/personal sources of happiness. Consistent with the literature, it was seen that socio-demographic variables impacted the levels of happiness in Turkey. The main findings show that marital status has the highest effect on perceived happiness, and married people are happier than the unmarried ones. Age has a negative, educational background has a positive effect. For employment status, it is notable that per diem employees are unhappy. Besides, a detailed perspective to researchers working towards increasing perceived happiness by evaluating the identified sub-groups of working individuals living in Turkey is provided.

Measuring the Accuracy of Aggregates Computed from a Statistical Register

The Italian National Statistical Institute (Istat) is currently engaged in a modernization programme that foresees a significant revision of the methods traditionally used for the production of official statistics. The main concept behind this transformation is the use of the Integrated System Statistical Registers, created by a massive integration of administrative archives and survey data. In this article, we focus on how to measure the accuracy of register estimates of a population total from measurements calculated at the unit level. We propose the global mean squared error (GMSE) as a statistical quantity suitable for measuring accuracy in the context of the production of official statistics. It can be defined to explicitly consider the main sources of uncertainty that may affect registers. The article suggests a feasible calculation strategy for the GMSE that allows National Statistical Institutes to build algorithms that can promptly be applied for each user request, thus improving the relevance, transparency and confidence of official statistics. Through a simulation study, we verified the efficacy of the proposed strategy.