Journal articles on the topic 'Small Econometric models'
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1
Bidabad, Bijan. "A Small Macro-Econometric Model." American Finance & Banking Review 4, no. 1 (June 4, 2019): 22–31. http://dx.doi.org/10.46281/amfbr.v4i1.287.
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Different sizes of macro-econometric models are used for different policy purposes. In this paper, we introduce a small macro-econometric model that includes macro-aggregates variables that can be solved dynamically and be used as a sample model to be estimated for other countries.
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Kaboudan, Mahmoud A. "Oil Revenue and Kuwait's Economy: An Econometric Approach." International Journal of Middle East Studies 20, no. 1 (February 1988): 45–66. http://dx.doi.org/10.1017/s0020743800057500.
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This paper presents a macroeconomic model for a small developing oil-exporting economy: Kuwait. The model is a simultaneous system of difference equations. Historic effects of changes in revenues from oil exports on the country's economic conditions are simulated. The model is then used to forecast these conditions through 1990, and to test two fiscal policy alternatives under the assumption that revenues from Kuwait's oil exports will remain constant from 1986 to 1990. The following are key words: developing economies; oil-exporting economies; Middle East economies; Kuwait; Kuwait's economy; policy models; macroeconomic models; econometric models; macroeconometric models; forecasting models; and policy models.
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Zadadaev, Sergey A., and Pavel B. Lukyanov. "SOFT COMPUTING AND SMALL DATA IN AN ECONOMETRIC STUDY OF NATIONAL DEVELOPMENT GOALS." SOFT MEASUREMENTS AND COMPUTING 11, no. 60 (2022): 65–71. http://dx.doi.org/10.36871/2618-9976.2022.11.006.
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The aim of the work was to model the mechanism of the influence of an exogenous resource variable on the predicted indicator of the national development goal, in which one model was selected from an infinite family of hypothetical resource allocation models within a year, reflecting the uncertainty inherent in soft computing. The study of problems based on small sample data in the age of big data is substantiated by the fact that there are a number of longitudinal tasks of longterm research in which, after 5–6 years of testing any methods, it is necessary to obtain data on their effectiveness and predictability in general. At the same time, the data slice occurs strictly at the end of the year as a control and summary measurement. In such cases, special econometric specifications of models are required that take into account the "physics" of relationships. This situation is similar to the situation in mechanics, when small data are compensated by the laws of motion and play the role of initial data in the Cauchy problem for differential equations – when the law itself is known and does not need to be estimated using big data.
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Vinod, H. D., and L. R. Shenton. "Exact Moments for Autor1egressive and Random walk Models for a Zero or Stationary Initial Value." Econometric Theory 12, no. 3 (August 1996): 481–99. http://dx.doi.org/10.1017/s0266466600006824.
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For a first-order autoregressive AR(1) model with zero initial value, xi = axi−1,_, + ei, we provide the bias, mean squared error, skewness, and kurtosis of the maximum likelihood estimator â. Brownian motion approximations by Phillips (1977, Econometrica 45, 463–485; 1978, Biometrika 65, 91–98; 1987, Econometrica 55, 277–301), Phillips and Perron (1988, Biometrika 75, 335–346), and Perron (1991, Econometric Theory 7, 236–252; 1991, Econometrica 59, 211–236), among others, yield an elegant unified theory but do not yield convenient formulas for calibration of skewness and kurtosis. In addition to the usual stationary case |α| < 1, we include the unstable |α| = 1 case of the random walk model. For the |α| < 1 case, we give new exact results for White's (1961, Biometrika 48, 85–94) model B, where the initial value x0 is a normal random variable N(0,σ2/(l – α2)). Our expressions are exact for small samples computed by relatively reliable Gaussian quadrature methods, rather than approximate ones in powers of n−l or α2.
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Nymoen, Ragnar. "On the Low Degree of Entropy Implied by the Solutions of Modern Macroeconomic Models." Entropy 24, no. 12 (November 25, 2022): 1728. http://dx.doi.org/10.3390/e24121728.
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The non-causal (“forward-looking”) solution used routinely in academic macroeconomics may represent a violation of a law of entropy, namely that the direction of time is one way (from the past and towards the present), and that the variance of economic processes increases with time. In order to re-establish a degree of compatibility with the law of entropy, so called hybrid forms are required add-ins to DSGE (Dynamic Stochastic General Equilibrium) models. However, the solution that uses hybrid forms is a particular special case of a causal solutions of autoregressive distributed lags, VARs and recursive and simultaneous equations models well known from empirical macro econometrics. Hence, hybrid forms of small scale DSGE models can be analysed and tested against competing model equations, using an econometric encompassing framework.
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Roljic, Lazo. "An expert system for national economy model simulations." Yugoslav Journal of Operations Research 12, no. 2 (2002): 247–69. http://dx.doi.org/10.2298/yjor0202247r.
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There are some fundamental economic uncertainties. We cannot forecast economic events with a very high scientific precision. It is very clear that there does not exist a unique 'general' model, which can yield all answers to a wide range of macroeconomic issues. Therefore, we use several different kinds of models on segments of the macroeconomic problem. Different models can distinguish/solve economy desegregation, time series analysis and other subfactors involved in macroeconomic problem solving. A major issue becomes finding a meaningful method to link these econometric models. Macroeconomic models were linked through development of an Expert System for National Economy Model Simulations (ESNEMS). ESNEMS consists of five parts: (1) small-scale short-term national econometric model, (2) Methodology of Interactive Nonlinear Goal Programming (MINGP), (3) data-base of historical macro-economic aggregates, (4) software interface for interactive communications between a model and a decision maker, and (5) software for solving problems. ESNEMS was developed to model the optimum macro-economic policy of a developing country (SFRY-formerly Yugoslavia). Most econometric models are very complex. Optimizing of the economic policy is typically defined as a nonlinear goal programming problem. To solve/optimize these models, a new methodology, MINGP, was developed as a part of ESNEMS. MINGP is methodologically based on linear goal programming and feasible directions method. Using Euler's Homogeneous Function Theorem, MINGP linearizes nonlinear homogeneous functions. The highest priorities in minimizing the objective function are the growth of gross domestic product and the decrease of inflation. In the core of the optimization model, MINGP, there is a small-scale econometric model. This model was designed through analysis of the causal relations in the SFRY's social reproduction process of the past 20 years. The objective of the econometric model is to simulate potential short term (one-year) national economic policies. Ex-ante simulation and optimization of economic policy for 1986 showed that, in SFRY, non-consistent macro-economic policy was resolute and led to both slower economic development and more rapid growth of inflation.
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Suryan, Viktor. "ECONOMETRIC FORECASTING MODELS FOR AIR TRAFFIC PASSENGER OF INDONESIA." Journal of the Civil Engineering Forum 3, no. 1 (August 29, 2017): 303. http://dx.doi.org/10.22146/jcef.26594.
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One of the major benefits of the air transport services operating in bigger countries is the fact that they provide a vital social economic linkage. This study is an attempt to establish the determinants of the passenger air traffic in Indonesia. The main objective of the study is to determine the economic variables that affect the number of airline passengers using the econometrics model of projection with an emphasis on the use of panel data and to determine the economic variables that affect the number of airline passengers using the econometrics model of projection with an emphasis on the use of time series data. This research also predicts the upcoming number of air traffic passenger until 2030. Air transportation and the economic activity in a country are interdependent. This work first uses the data at the country level and then at the selected airport level for review. The methodology used in this study has adopted the study for both normal regression and panel data regression techniques. Once all these steps are performed, the final equation is taken up for the forecast of the passenger inflow data in the Indonesian airports. To forecast the same, the forecasted numbers of the GDP (Gross Domestic Product) and population (independent variables were chosen as a part of the literature review exercise) are used. The result of this study shows the GDP per capita have significant related to a number of passengers which the elasticity 2.23 (time-series data) and 1.889 for panel data. The exchange rate variable is unrelated to a number of passengers as shown in the value of elasticity. In addition, the total of population gives small value for the elasticity. Moreover, the number of passengers is also affected by the dummy variable (deregulation). With three scenarios: low, medium and high for GDP per capita, the percentage of growth for total number of air traffic passenger from the year 2015 to 2030 is 199.3%, 205.7%, and 320.9% respectively.
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Doszyń, Mariusz. "Econometric Models of Real Estate Prices with Prior Information. Mixed Estimation." Real Estate Management and Valuation 30, no. 3 (September 1, 2022): 61–72. http://dx.doi.org/10.2478/remav-2022-0021.
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Abstract The purpose of this paper is to estimate econometric models with sample and prior information. Prices of land property for residential development in Szczecin are modeled (the price level was determined for 2018). Modeling property prices only based on sample data generates numerous problems. Transaction databases from local real estate markets often contain a small number of observations. Properties are frequently similar, which results in low variability of property characteristics, and thus – low efficiency of parameter estimators. In such a situation, the impact of some features cannot be estimated from the sample data. As a solution to this problem, the paper proposes econometric models that consider prior information. This information can be, for example, in the form of property feature weights proposed by experts. The prior information will be expressed in the form of stochastic restrictions imposed on the model parameters. In the simulation experiment, the predictive power of mixed estimation models is compared with two kind of models: OLS models and model with only prior information. It turned out that mixed estimation results are superior with regard to formal criteria and predictive abilities.
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Svetlana V. Doroshenko Ksenia A. Posysoeva, Svetlana V. Doroshenko Ksenia A. Posysoeva, and Svetlana V. Doroshenko Ksenia A. Posysoeva Svetlana V. Doroshenko Ksenia A. Posysoeva. "Econometric Estimation of Strategic Development Factors of Russian Border Regions." Economy of Region 17, no. 2 (June 2021): 431–44. http://dx.doi.org/10.17059/ekon.reg.2021-2-6.
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Cross-border development is significantly influenced by global events, such as 1990s transformations, when different inland areas across the world became borderlands. Further, due to 2014 geopolitical changes, the Russian Federation had to establish a new institutional framework regulating the border regional development. The research aims to assess the impact of strategic factors on socio-economic development of these regions. For that purpose, we analysed 47 of 50 Russian border entities divided into two groups of old and new (established after the collapse of the USSR in 1991) border regions. We hypothesise that the factors considered as strategic in these territories manifest differently in old and new border regions. Empirical data, obtained from the Federal State Statistics Service and Unified Interdepartmental Statistical Information System, cover the period from 2000 to 2018. The simulation was conducted using the statistical package Stata 14. We analysed five groups of factors (transport infra- structure, small business, foreign trade, tourism, ecology) as well as corresponding indicators. Gross regional product per capita in comparable prices of 2018 was considered as a dependent variable. Then, we assessed three models explaining the impact of the examined factors on old and new border regions individually and in combination. For each model, pooled regression, as well as random and fixed effects models were constructed. Conducted simulations revealed that the fixed effects models best describe the analysed data. The research results confirmed the hypothesis, showing that transport infrastructure and tourism are more important for new border regions, while the factors of ecology, small business and foreign trade have a greater impact on the development of old borderlands.
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Surmann, Markus, Wolfgang Brunauer, and Sven Bienert. "How does energy efficiency influence the Market Value of office buildings in Germany and does this effect increase over time?" Journal of European Real Estate Research 8, no. 3 (November 2, 2015): 243–66. http://dx.doi.org/10.1108/jerer-04-2015-0018.
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Purpose – The paper aims to estimate the effect of energy efficiency on the Market Value of office buildings and consider whether this effect increases over time. Design/methodology/approach – The authors analyze a dataset of office building valuations from 2009 to 2011, provided by the German Investment Property Database. The authors use hedonic regression models to determine the effect of energy efficiency and energy consumption on Market Values. Using generalized additive models (GAM) for modeling nonlinear covariate effects, the authors control for further building characteristics and location. Due to the small sample size, the authors introduce an innovative econometric approach that mitigates this problem. Findings – Mainly due to the small sample size, and in spite of the newly developed econometric methodology, the authors do not find clear evidence of the relationship between energy efficiency and the Market Value. However, the study nonetheless provides interesting insights into the composition of office building Market Values in Germany. Originality/value – In addition to the empirical results for the German office market, the main contribution of this paper lies in the econometric methodology. Beside the application of cutting-edge statistical techniques, the authors develop a method for handling datasets, for which the variable of interest is rarely observed, leveraging on the total available data. Thus, the methodology offers promising prospects for future research in similar settings.
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Sheng, Shuyang. "A Structural Econometric Analysis of Network Formation Games Through Subnetworks." Econometrica 88, no. 5 (2020): 1829–58. http://dx.doi.org/10.3982/ecta12558.
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The objective of this paper is to identify and estimate network formation models using observed data on network structure. We characterize network formation as a simultaneous‐move game, where the utility from forming a link depends on the structure of the network, thereby generating strategic interactions between links. With the prevalence of multiple equilibria, the parameters are not necessarily point identified. We leave the equilibrium selection unrestricted and propose a partial identification approach. We derive bounds on the probability of observing a subnetwork, where a subnetwork is the restriction of a network to a subset of the individuals. Unlike the standard bounds as in Ciliberto and Tamer (2009), these subnetwork bounds are computationally tractable in large networks provided we consider small subnetworks. We provide Monte Carlo evidence that bounds from small subnetworks are informative in large networks.
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Rudzkis, Rimantas, and Roma Valkavičienė. "ECONOMETRIC MODELS OF THE IMPACT OF MACROECONOMIC PROCESSES ON THE STOCK MARKET IN THE BALTIC COUNTRIES." Technological and Economic Development of Economy 20, no. 4 (December 16, 2014): 783–800. http://dx.doi.org/10.3846/20294913.2014.949901.
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The article examines the dependencies of individual sectoral stock price indices of OMX Baltic security market on macroeconomic indicators, using econometric methods. Regression models are constructed using quarterly time series of 2000–2011 years while the methodology is backed with the findings of Lithuanian and foreign scientists from an extensive overview of specific literature. Regression equations, obtained in the paper, allows us to identify the key macroeconomic and global indicators that statistically significantly affect the Baltic securities market and to quantify their impact on the stock price indices of individual sectors in the Baltic countries. Econometric analysis of OMX Baltic security market proves the hypothesis that the set of macroeconomic regressors may vary considerably depending on the individual sector's price indices, especially in the case of small open economy with immature stock markets. The paper provides investors who are shaping their portfolios taking into account the macroeconomic forecasts with additional opportunities on the basis of sectoral stock price indices regression equations.
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Morley, James, Irina B. Panovska, and Tara M. Sinclair. "TESTING STATIONARITY WITH UNOBSERVED-COMPONENTS MODELS." Macroeconomic Dynamics 21, no. 1 (March 8, 2016): 160–82. http://dx.doi.org/10.1017/s1365100515000437.
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In the aftermath of the global financial crisis, competing measures of the trend in macroeconomic variables such as U.S. real GDP have featured prominently in policy debates. A key question is whether large shocks to macroeconomic variables will have permanent effects—i.e., in econometric terms, do the data contain stochastic trends? Unobserved-components models provide a convenient way to estimate stochastic trends for time series data, with their existence typically motivated by stationarity tests that allow at most a deterministic trend under the null hypothesis. However, given the small sample sizes available for most macroeconomic variables, standard Lagrange multiplier tests of stationarity will perform poorly when the data are highly persistent. To address this problem, we propose the use of a likelihood ratio test of stationarity based directly on the unobserved-components models used in estimation of stochastic trends. We demonstrate that a bootstrap version of this test has far better small-sample properties for empirically relevant data-generating processes than bootstrap versions of the standard Lagrange multiplier tests. An application to U.S. real GDP produces stronger support for the presence of large permanent shocks using the likelihood ratio test than using the standard tests.
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Kuethe, Todd Henry. "International Real Estate Review." International Real Estate Review 14, no. 1 (April 30, 2011): 118–29. http://dx.doi.org/10.53383/100136.
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This study evaluates the ability of a range of popular aggregate house price indexes to predict house prices out-of- sample at the transaction level for a small geographic area. The analysis particularly addresses the utility of spatial econometric methods. The results suggest that spatial econometric methods, which more explicitly consider the spatial aspects of observed house prices, provide better predictive accuracy as compared to more traditional estimation techniques, such as the repeat sales index, a hybrid repeat sales-hedonic price index, and hedonic price models estimated through least squares. The conclusions are drawn from a sample of 38,984 single-family residential real estate transactions for the city of Milwaukee, Wisconsin over the years 2002-2008.
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Phillips, Peter C. B. "Trending Multiple Time Series: Editor's Introduction." Econometric Theory 11, no. 5 (October 1995): 811–17. http://dx.doi.org/10.1017/s0266466600009890.
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One of the more obvious empirical characteristics of macroeconomic time series is their tendency to grow, or trend, over time. Dealing with this trendnonstationarity in models of multiple time series has been a major agenda of econometric research for much of the last decade and has produced an enormous literature. Equally, the goal of developing a general asymptotic theory of inference for stochastic processes has been a long-standing concern of probabilists and statisticians. Finally, understanding and modeling trend processes and cyclical activity lie at the nerve center of much of modern macroeconomics. As a consequence, research on nonstationary time series has brought statisticians, econometricians, and macroeconomists close together in productive ways that simply could not have been anticipated 10 years ago.The focus of this symposium issue of Econometric Theory is inference from multiple time series data with trends, and the symposium brings together researchers with these diverse interests. The papers included in the issue were, with two exceptions, presented at a conference called “Trending Multiple Time Series,” held at Yale University in the fall of 1993 under the financial sponsorship of the National Science Foundation. All of the papers were written by conference participants. The conference was the fourth in a series of small conferences at Yale on the general theme of “Applications of Functional Limit Theory to Econometrics and Statistics.”
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Partachi, Ion, and Valentin Popa. "ECONOMETRIC APPROACHES IN ANALYZING RESEARCH AND INNOVATION SMES ACTIVITY IN BUCHAREST." Economica, no. 1(119) (April 2022): 93–103. http://dx.doi.org/10.53486/econ.2022.119.093.
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Comparative analysis, in the light of statistical evolution indicators that characterize the innovative activity of SMEs in Bucharest, aims to outline the companies situation, over a period of almost 20 years. Analysis in dynamics, with the latest available indicators data, concerns not only the situation at the Bucharest municipality level at a certain time, but also the comparison with similar SMEs indicators with research and development-innovation (RDI) activity in Romania. Econometric approaches pursue the goal of developing appropriate models for this period and of producing short-term predictions, and the criteria for choosing the prediction accuracy, they allow us to draw pertinent conclusions. To quantify the existing situation regarding SMEs, a rather small number of indicators have been taken into account, due to the lack of their dissemination
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Wiśniewski, Jerzy Witold. "Forecasting in Small Business Management." Risks 9, no. 4 (April 9, 2021): 69. http://dx.doi.org/10.3390/risks9040069.
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This work aims to verify an authorial forecasting method from a system of interdependent equations, which is based on empirical equations of the structural form and is mainly intended for econometric micromodels. The prediction procedure will be analogous to the so-called chain prediction that is used for recursive models. The difference—compared with the prediction from a recursive model—entails the necessity of using one of the reduced-form empirical equations to begin the procedure of constructing a sequence of forecasts from successive structural-form empirical equations. The research results presented above indicate that the above-proposed iterative forecasting method from structural-form equations of a system of interdependent equations guarantees synchronization of forecasts as part of a closed cycle of relations. A different number of iterations is required to obtain convergent forecasts. It can be noticed that the further ahead the forecasted period is, the more iterations should be carried out to obtain convergent forecasts. Small business management with the use of forecasting can be done remotely. Rapid updates of statistical information will require cloud-based communication. Completion of data in a cloud will allow, on one hand, accurate assessment of expired forecasts and, on the other, to update the predictor equations. This can be carried out at any place with Internet access.
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Többen, Johannes Reinhard, Martin Distelkamp, Britta Stöver, Saskia Reuschel, Lara Ahmann, and Christian Lutz. "Global Land Use Impacts of Bioeconomy: An Econometric Input–Output Approach." Sustainability 14, no. 4 (February 9, 2022): 1976. http://dx.doi.org/10.3390/su14041976.
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Many countries have set ambiguous targets for the development of a bioeconomy that not only ensures sufficient production of high-quality foods but also contributes to decarbonization, green jobs and reducing import dependency through biofuels and advanced biomaterials. However, feeding a growing and increasingly affluent world population and providing additional biomass for a future bioeconomy all within planetary boundaries constitute an enormous challenge for achieving the Sustainable Development Goals (SDG). Global economic models mapping the complex network of global supply such as multiregional input–output (MRIO) or computable general equilibrium (CGE) models have been the workhorses to monitor the past as well as possible future impacts of the bioeconomy. These approaches, however, have often been criticized for their relatively low amount of detail on agriculture and energy, or for their lack of an empirical base for the specification of agents’ economic behavior. In this paper, we address these issues and present a hybrid macro-econometric model that combines a comprehensive mapping of the world economy with highly detailed submodules of agriculture and the energy sector in physical units based on FAO and IEA data. We showcase the model in a case study on the future global impacts of the EU’s bioeconomy transformation and find small positive economic impacts at the cost of a considerable increase in land use mostly outside of Europe.
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Rahman, Mohamad Miftah, Dodi Nandika, and Bintang Charles Hamonangan Simangunsong. "Demand Analysis of Termite Control Service in Jakarta." Jurnal Sylva Lestari 8, no. 1 (January 27, 2020): 10. http://dx.doi.org/10.23960/jsl1810-19.
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Termite is an economically important pest species in the pest control industry and considered as one of the urban pests. Although it had caused a great loss, only a few studies on termite control demand were found. This study attempted to identify determinants and build the econometric model of termite control demand in Jakarta. The findings are expected to give the pest control industry a better understanding of the pest control market. Two ad-hoc models, linear and double log models, were investigated using the Least Square Dummy Variable (LSDV) technique. The results showed that the double log model was found better than the linear model based on sign expectation and significance. The price of termite control service, building permits, price of structural metals and dummy variables for the large company were statistically significant determinants, whereas dummy variables for risk class were not. Termite control demand for medium and small companies was not significantly different, but both of them were significantly lower than demand for the large company. This study also found that the demand for termite control was elastic.Keywords: demand analysis, econometric modeling, pest control, termite control, urban pest
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KOPSIDIS, MICHAEL, and DANIEL W. BROMLEY. "The French revolution and German industrialization: dubious models and doubtful causality." Journal of Institutional Economics 12, no. 1 (July 2, 2015): 161–90. http://dx.doi.org/10.1017/s1744137415000223.
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AbstractWe challenge the ‘big-bang’ approach to economic history offered by Acemogluet al.(2011). The creation story in dispute is the French Revolution and the subsequent French occupation of a very small portion of Germany. We show that the four institutional reforms claimed to have spurred German industrialization have been incorrectly dated. These corrections nullify any explanatory power of the ACJR econometric model. Moreover, even with the corrected vintages, their identification strategy is undermined by a flawed ‘explanatory’ variable – ‘years of reform’. We show that this variable simply enters their model as a year trend and explains nothing except the passage of time. We develop a fixed-effects model to capture the overlooked role of coal production that began in several regions shortly after 1840. This model offers a credible account of German industrialization and urbanization. Most economic change is, after all, continuous. Big-bang intrusions are of doubtful efficacy.
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Juhl, Ted, and Zhijie Xiao. "NONPARAMETRIC TESTS OF MOMENT CONDITION STABILITY." Econometric Theory 29, no. 1 (May 21, 2012): 90–114. http://dx.doi.org/10.1017/s0266466612000151.
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This paper considers testing for moment condition instability for a wide variety of models that arise in econometric applications. We propose a nonparametric test based on smoothing the moment conditions over time. The resulting test takes the form of a U-statistic and has a limiting normal distribution. The proposed test statistic is not affected by changes in the distribution of the data, so long as certain simple regularity conditions hold. We examine the performance of the test through a small Monte Carlo experiment.
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Prišenk, Jernej, and Jernej Turk. "Assessment of Concept between Rural Development Challenges and Local Food Systems: A Combination between Multi-Criteria Decision Analysis and Econometric Modelling Approach." Sustainability 14, no. 6 (March 16, 2022): 3477. http://dx.doi.org/10.3390/su14063477.
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This study investigates the influence of social, economic, and environmental impacts on the promotion and marketing systems of local food products from mountain areas in Slovenia. These impacts were assessed using an econometric modelling approach. Two econometric models were developed (one for production and one for marketing). The case studies of local food products were selected from Slovenian mountain regions, most of which were from less-favored areas (LFAs). A majority of the selected food commodities were of high quality, with or without protected designations. Data collection was carried out via interviews. Due to production limitation on mountain areas in Slovenia and other constraints in LFAs, the socio-economic and environmental impacts on success of production and marketing systems need to be clarified. These relations present a potential impact on the wider socio-economic development in the region. The empirical results, obtained using an econometric modelling approach, clearly show the importance of encouraging the socio-economic and environmental impacts in ensuring the marketing and production potentials of local food products. The result express good relationships, and cooperation between the actors in the food supply chains contributing to a successful marketing system and production system of local food products (small, average, large) is dependent on the available local labour in mountain rural areas.
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Thrane, Christer. "Modelling tourists’ length of stay." Tourism Economics 22, no. 6 (September 21, 2016): 1352–66. http://dx.doi.org/10.5367/te.2015.0489.
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Modelling of tourists’ length of stay (LOS) is an expanding topic of study. A common thread in this literature is the use of sophisticated statistical/econometric methods. The present study builds on and extends an article critical of the statistical craftsmanship in prior LOS modelling studies. On the basis of an updated assessment of current practice and two small-scale case studies, two main conclusions are drawn. First, the available evidence suggests that the ordinary least squares (OLS) regression model produces qualitatively similar findings to much more complicated methods, such as duration and count data models. The principle of parsimony and the so-called KISS rule thus dictate that OLS regression analysis should be the preferred estimation technique in LOS modelling studies. Second, the quality of LOS modelling studies will most likely be improved by intensifying the use of the long-established tools of the trade explicated in influential econometric textbooks rather than by testing new estimation methods.
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Ye, Shun, Honggen Xiao, Tianyu Ying, and Lingqiang Zhou. "Determinants of small accommodation business size." International Journal of Contemporary Hospitality Management 31, no. 4 (April 8, 2019): 1626–46. http://dx.doi.org/10.1108/ijchm-04-2018-0290.
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PurposeThis paper aims to model and empirically test the determinants of small accommodation business (SAB) size.Design/methodology/approachThis study distinguishes among three aspects of SAB size (accommodation scale, investment and employment) and between two modes of growth (managerial and entrepreneurial growth). A conceptual framework was developed based on business growth theory, whereby three econometric models were constructed and estimated to predict size variations. Data were collected through a survey on 200 SABs in North Zhejiang Province of China. Effects of the determinants were contrasted between different size indicators.FindingsThe SAB size can be affected by personal factors (employed working experience, education level, industry-specific know-how), interpersonal factor (relative ties to other SABs) and environmental factor (association support). The interpersonal and environmental factors tend to contribute to managerial growth, while the personal factors are usually conducive to entrepreneurial growth.Research limitations/implicationsThis study addresses the questions of “why some SABs grow larger in size than others” and “why different SABs grow in different ways”. But more contexts and business types should be examined so as to ensure generalizability through future studies.Practical implicationsThe research findings can provide guidelines for local tourism administration to encourage or regulate SAB development.Originality/valueThis study is among the first endeavors to examine the multidimensionality and determinants of business size in tourism and hospitality; it contributes to literature by expanding tourism entrepreneurship research into a/the “growth paradigm”.
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Pasaribu, Pananda. "Female Directors and Firm Performance: Evidence from UK Listed Firms." Gadjah Mada International Journal of Business 19, no. 2 (August 23, 2017): 145. http://dx.doi.org/10.22146/gamaijb.15619.
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The impact of female directors on firm performance has lacked consistency in the previously conducted empirical studies, which may be due to the endogeneity problem, or certain characteristics (i.e. governance, industry, competition). This study examines the relationship between female directors and firm performance by addressing those problems. This study analyses all non-financial UK listed firms during the period 2004-2012 and employs several econometric models. The regression results indicate that there is little evidence that female directors have a positive and strong relationship with firm performance. But, further analysis reports that the UK’s small listed firms experience a positive significant effect, because small firms do not suffer from the problem of over-monitoring and they have more flexibility in composing their boards of directors.
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Kowerski, Mieczysław, Małgorzata Wolańczyk, and Mariusz Poninkiewicz. "A Proposition for a Methodology to Assess the Influence of European Union Funds on Living Conditions among Citizens of a Commune." Barometr Regionalny. Analizy i Prognozy 13, no. 3 (October 27, 2015): 105–16. http://dx.doi.org/10.56583/br.741.
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In this paper a two phase methodology to assess the influence of the European Union funds on living conditions among citizens of a commune was proposed. During the first the total index of living conditions in a given commune during a specific time period is calculated. During the second phase econometric logit models of the dependence of the total index on the share of the EU funds invested in a given commune are constructed. The developed methodology has been illustrated with calculations concerning the small, rural commune Zarzecze from the Podkarpackie Voivodship during the years 2003–2013.
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Rzymowski, Witold, and Agnieszka Surowiec. "Modelling Population Growth with Difference Equation Method." Przegląd Statystyczny 64, no. 3 (September 30, 2017): 339–52. http://dx.doi.org/10.5604/01.3001.0014.0826.
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In this paper, we present a new method of the econometric model construction: the difference equation method. We illustrate the proposed approach using an application example from human population dynamic study. We find out that proposed method is very useful to find one of the three forms of proposed models of human population satisfying the small maximal relative errors. The maximal relative error is a measure to verify the model of human population. The proposed method is tested for all available data referring to the human population in the OECD countries as well as in selected non-OECD countries.
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Enders, Walter, and Gary A. Hoover. "The Nonlinear Relationship between Terrorism and Poverty." American Economic Review 102, no. 3 (May 1, 2012): 267–72. http://dx.doi.org/10.1257/aer.102.3.267.
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In spite of the common wisdom that poverty breeds terrorism, econometric tests usually find that terrorism is influenced by population and various measures of democratic freedom, but not per capita GDP. Unlike previous studies, we use a data set containing separate measures of domestic and transnational terrorism and estimate models allowing for a nonlinear relationship between terrorism and poverty. When we account for the nonlinearities in the data and distinguish between the two types of terrorist events, we find that poverty has as a very strong influence on domestic terrorism and a small, but significant, effect on transnational terrorism.
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Antoine, Bertille, Kevin Proulx, and Eric Renault. "Pseudo-True SDFs in Conditional Asset Pricing Models*." Journal of Financial Econometrics 18, no. 4 (September 18, 2018): 656–714. http://dx.doi.org/10.1093/jjfinec/nby017.
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Abstract This article is motivated by the need to bridge some gap between modern asset pricing theory and recent developments in econometric methodology. While asset pricing theory enhances the use of conditional pricing models, econometric inference of conditional models can be challenging due to misspecification or weak identification. To tackle the case of misspecification, we utilize the conditional Hansen and Jagannathan (1997) (HJ) distance as studied by Gagliardini and Ronchetti (2016), but we set the focus on interpretation and estimation of the pseudo-true value defined as the argument of the minimum of this distance. While efficient Generalized Method of Moments (GMM) has no meaning for estimation of a pseudo-true value, the HJ-distance not only delivers a meaningful loss function, but also features an additional advantage for the interpretation and estimation of managed portfolios whose exact pricing characterizes the pseudo-true pricing kernel (stochastic discount factor (SDF)). For conditionally affine pricing kernels, we can display some managed portfolios which are well-defined independently of the pseudo-true value of the parameters, although their exact pricing is achieved by the pseudo-true SDF. For the general case of nonlinear SDFs, we propose a smooth minimum distance (SMD) estimator (Lavergne and Patilea, 2013) that avoids a focus on specific directions as in the case of managed portfolios. Albeit based on kernel smoothing, the SMD approach avoids instabilities and the resulting need of trimming strategies displayed by classical local GMM estimators when the density function of the conditioning variables may take arbitrarily small values. In addition, the fact that SMD may allow fixed bandwidth asymptotics is helpful regarding the curse of dimensionality. In contrast with the true unknown value for a well-specified model, the estimated pseudo-true value, albeit defined in a time-invariant (unconditional) way, may actually depend on the choice of the state variables that define fundamental factors and their scaling weights. Therefore, we may not want to be overly parsimonious about the set of explanatory variables. Finally, following Antoine and Lavergne (2014), we show how SMD can be further robustified to deal with weaker identification contexts. Since SMD can be seen as a local extension of the method of jackknife GMM (Newey and Windmeijer, 2009), we characterize the Gaussian asymptotic distribution of the estimator of the pseudo-true value using classical U-statistic theorems.
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Koçiu, Lorenc, and Kledian Kodra. "Using the Econometric Models for Identification of Risk Factors for Albanian Smes (Case Study: Smes of Gjirokastra Region)." WSEAS TRANSACTIONS ON BUSINESS AND ECONOMICS 18 (January 5, 2021): 163–70. http://dx.doi.org/10.37394/23207.2021.18.17.
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Using the econometric models, this paper addresses the ability of Albanian Small and Medium-sizedEnterprises (SMEs) to identify the risks they face. To write this paper, we studied SMEs operating in theGjirokastra region. First, qualitative data gathered through a questionnaire was used. Next, the 5-level Likertscale was used to measure it. Finally, the data was processed through statistical software SPSS version 21,using the binary logistic regression model, which reveals the probability of occurrence of an event when allindependent variables are included. Logistic regression is an integral part of a category of statistical models,which are called General Linear Models. Logistic regression is used to analyze problems in which one or moreindependent variables interfere, which influences the dichotomous dependent variable. In such cases, the latteris seen as the random variable and is dependent on them. To evaluate whether Albanian SMEs can identifyrisks, we analyzed the factors that SMEs perceive as directly affecting the risks they face. At the end of thepaper, we conclude that Albanian SMEs can identify risk
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Arvin-Rad, Hassan. "Comparison of Deterministic and Stochastic Predictors in Nonlinear Systems When the Disturbances Are Small." Econometric Theory 13, no. 3 (June 1997): 368–91. http://dx.doi.org/10.1017/s0266466600005855.
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This paper compares the deterministic and stochastic predictors of nonlinear models when the disturbances are small. Large-sample properties of these predictors have been analyzed extensively in the econometric literature. While the deterministic predictors are asymptotically biased, there are some Monte Carlo experiments that suggest the magnitude of this bias is rather insignificant. Here, we offer a possible explanation of the smallness of the deterministic bias. It is shown that when the error terms have small standard deviation, the deterministic predictor turns out to be asymptotically unbiased. The results are based on deriving asymptotic expansions for alternative predictors. The asymptotic expansions carried out here are similar to the large-sample asymptotic expansions; however, the expansions here are in terms of the standard deviation of the disturbance terms. The results are then used to obtain the asymptotic bias and asymptotic mean squared prediction errors of the deterministic and stochastic predictors of a model containing the Box-Cox transformation.
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Krejcí, Martin, Wadim Strielkowski, and Inna Čabelková. "Factors that influence the success of small and medium enterprises in ICT: a case study from the Czech Republic." Verslas: Teorija ir Praktika 16, no. 3 (October 1, 2015): 304–15. http://dx.doi.org/10.3846/btp.2015.521.
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Small and medium enterprises (SMEs) occupy a large niche in the information and technology sector (ICT) and play an important role in the functioning on any state’s economy. This paper focuses on a specific local market and uses the Czech Republic as a case study in order to establish the success factors crucial for achieving economic success. It aims at determining those factors with the help of econometric success rate models based on the own data collected via the means of questionnaire survey among ICT enterprise. Our results show that the earnings-employee ratio, average revenues and the investment in own R&D play the most important role in the success of Czech SMEs in question. Both, financial and non-financial indicators perform significantly in the predictions of success.
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Davia, María A., and Nuria Legazpe. "Decisiones laborales de las mujeres casadas o cohabitantes en España." Studies of Applied Economics 30, no. 3 (June 7, 2020): 1065. http://dx.doi.org/10.25115/eea.v30i3.3618.
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The aim of this paper is to analyse the determinants of employment decisions (entry and exit from employment) of married or cohabiting women in Spain. We use the Fertility, Family and Values Survey of 2006, conducted by the Sociological Research Centre in 2006. The econometric technique deployed consists in different discrete-time duration models using Meyer’s application (Meyer, 1990) to Prentice-Gloeckler model (1978) that enables control for unobserved heterogeneity. The results show, among other things, that highly educated women and women from more recent cohorts are more likely to (re-)enter the labour market after marriage. Mothers of small children are more likely to exit employment than non-mothers.
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Alwee, Razana, Siti Mariyam Hj Shamsuddin, and Roselina Sallehuddin. "Hybrid Support Vector Regression and Autoregressive Integrated Moving Average Models Improved by Particle Swarm Optimization for Property Crime Rates Forecasting with Economic Indicators." Scientific World Journal 2013 (2013): 1–11. http://dx.doi.org/10.1155/2013/951475.
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Crimes forecasting is an important area in the field of criminology. Linear models, such as regression and econometric models, are commonly applied in crime forecasting. However, in real crimes data, it is common that the data consists of both linear and nonlinear components. A single model may not be sufficient to identify all the characteristics of the data. The purpose of this study is to introduce a hybrid model that combines support vector regression (SVR) and autoregressive integrated moving average (ARIMA) to be applied in crime rates forecasting. SVR is very robust with small training data and high-dimensional problem. Meanwhile, ARIMA has the ability to model several types of time series. However, the accuracy of the SVR model depends on values of its parameters, while ARIMA is not robust to be applied to small data sets. Therefore, to overcome this problem, particle swarm optimization is used to estimate the parameters of the SVR and ARIMA models. The proposed hybrid model is used to forecast the property crime rates of the United State based on economic indicators. The experimental results show that the proposed hybrid model is able to produce more accurate forecasting results as compared to the individual models.
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Mazzoleni, Alberto, and Enrica Pollonini. "Factors driving indebtedness among small- and medium-sized dairy companies." British Food Journal 123, no. 1 (July 7, 2020): 159–75. http://dx.doi.org/10.1108/bfj-04-2020-0341.
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PurposeWe developed a model to demonstrate how multiple interrelated aspects of a firm influence its recourse to third-party financing, which frequently depends on the characteristics of each food production chain.Design/methodology/approachWe conducted an empirical research on a relevant sample of small- and medium-sized Italian dairy firms. Our research methodology is inspired by the grounded theory (Glaser and Strauss, 1967).FindingsOur findings illustrated that firm indebtedness is the result of intertwined variables, linked to different firm dimensions, including growth, financial structure and economic dynamics.Research limitations/implicationsA portion of the analysed phenomenon is not explained using the sample and econometric tools.Practical implicationsThere are practical implications for the decision-makers in a firm (in particular, the managers and the shareholders) as the model allows to evaluate the influence of a set of mutually interdependent firm variables for the indebtedness level.Originality/valueFirst, we considered the recourse to third-party financing within the context of the systems theory (Millová and Blatný, 2015) and from the perspective of linked causes and mutually connected variables. Second, our research focussed on a well-defined food chain and on features of firms operating in this context. Last, our model considered the impact of the recent economic crisis, which motivated us to review the existing models.
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Casinillo, Leomarich F., and Emily L. Casinillo. "Econometric Modelling on Happiness in Learning Mathematics: The Case of Senior High Students." Indonesian Journal of Curriculum and Educational Technology Studies 8, no. 1 (April 29, 2020): 22–31. http://dx.doi.org/10.15294/ijcets.v8i1.38031.
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This study developed econometric models on the students’ happiness in learning mathematics to identify its influencing factors. A complete enumeration of 115 grade 11 students in the Visayas State University were employed as participants. Results showed that about 61% of the students considered themselves as moderately happy in learning. Their expected happiness is approximately the same with their actual happiness, which is one of the significant determinants in the models. STEM students among other strands in senior high school are more likely happy learners. Household income, allowance, and mental health condition show a small influence on their happiness in learning. Students who spend more time in the library, and those living in rural places tend to be happy in learning. Furthermore, physical health condition shows an inverse effect on students’ well-being in learning mathematics, while social relationships and the distance from home to school do not contribute to their happiness.
Abstrak
Penelitian ini mengembangkan model ekonometrik pada kebahagiaan siswa dalam pembelajaran matematika untuk mengidentifikasi faktor-faktor yang memengaruhinya. Data diambil dari 115 mahasiswa kelas 11 di Universitas Negeri Visayas. Hasilnya menunjukkan bahwa sekitar 61% mahasiswa menilai diri mereka relatif bahagia. Tingkat kebahagiaan yang mereka harapkan relatif sama dengan yang mereka tunjukkan secara aktual dan ini merupakan salah satu model yang signifikan buktinya. Siswa yang mengikuti program STEM dan sejenisnya pada jenjang sekolah menengah atas (SMA) tampak lebih bahagia. Pendapatan di rumah, tunjangan, dan kesehatan mental tampak menunjukkan pengaruh yang tidak seberapa pada kebahagiaan belajar. Sementara itu siswa yang menghabiskan banyak waktu di perpustakaan dan tinggal di perdesaan cenderung bahagia dalam belajar. Lebih lanjut, kondisi kesehatan fisik tampak berbanding terbalik dengan kesejahteraan siswa dalam belajar matematika, sementara itu relasi sosial dan jarak rumah ke sekolah tidak berkontribusi pada kebahagiaan siswa.
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Carruthers, Bruce G., Timothy W. Guinnane, and Yoonseok Lee. "Bringing “Honest Capital” to Poor Borrowers: The Passage of the U.S. Uniform Small Loan Law, 1907–1930." Journal of Interdisciplinary History 42, no. 3 (November 2011): 393–418. http://dx.doi.org/10.1162/jinh_a_00256.
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The Uniform Small Loan Law (usll)—the primary tool of the Russell Sage Foundation (rsf) intended to improve credit conditions for poor people in the United States during first decades of the twentieth century—created a new class of lenders who could legally make small loans at interest rates exceeding those allowed for banks. By the 1930s, about two-thirds of the states had passed the usll. Econometric models show that urbanization, state-level economic characteristics, and the nature of a state's banking system all affected the chance of passage. That party-political affiliations had no effect is consistent with the usll's “progressive” character. The passage of the usll in one state, however, made passage less likely in neighboring or similar states. The evidence suggests that the rsf only imperfectly understood the political economy of the usll, and that a different overall approach might have produced a result closer to its real aims.
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Andrei, Jean Vasile, Luminita Chivu, Ileana Georgiana Gheorghe, Aleksandar Grubor, Teodor Sedlarski, Violeta Sima, Jonel Subić, and Mile Vasic. "Small and Medium-Sized Enterprises, Business Demography and European Socio-Economic Model: Does the Paradigm Really Converge?" Journal of Risk and Financial Management 14, no. 2 (February 4, 2021): 64. http://dx.doi.org/10.3390/jrfm14020064.
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Although the European business environment induces important premises and assures conditions in determining economic growth and social well-being, the determinant and existent connections between the evolution of small and medium-sized enterprises (SMEs), business demography characteristics and the European socio-economic model have been scarcely studied in recent years. The dimensions of the European socio-economic model design a very specific framework in developing business demography and assuring a favorable environment for future SME development. The main aim of the manuscript is to investigate the evolution of the European SMEs sector and the perspective of business demography evolution to converge with exigencies of the European socio-economic model. In order to argue the research objective, eight specific and representative business demography variables were employed, from 12 European Union member states (EU-MS), during 2009–2017. Further, the SMEs’ performances, determined by changing the economic functional paradigm, were assessed. For proving this, an econometric model was designed considering labor productivity as an endogenous variable. Our preliminary analysis shows considerable differences in business demography indicators and SMEs development among all five socio-economic sub-models of the main European socio-economic model, proving a tight connection between European socio-economic models and SMEs’ performance and arguing the necessity of a paradigm convergence. Within some sub-models, there is clear evidence of clustering and convergence in terms of business demography and SMEs future development.
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Safaynikou, Hamid, Mohammad Taher Ahmadi Shadmehri, Ahmad Sabahi, and Mohammad Javad Razmi. "Modeling the Effective Factors on Bank Loans Default Rate UsingDelphi, SEM and Tobit Techniques (Evidence from Iran)." Modern Applied Science 11, no. 4 (January 24, 2017): 13. http://dx.doi.org/10.5539/mas.v11n4p13.
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Banks entering a developing market face a lot of uncertainty about the risks involved in lending. This paper models the effective factors on default rate (DR) loans to small and medium size enterprises (SMEs) in Iran based on the case study of branches of Melli Bank in Khorasan Razavi province. For this purpose a set of data about loans made to 300 SMEs between years 2004 to 2015 and Delphi, SEM and Tobit models were applied. Results of Delphi technique indicated that 48 factors affect the DR. The structural equation model (SEM) estimations showed that between 10 latent variables which describe the DR, the “loans properties” latent variable have the most effect. Also, findings of Tobit econometric model stated that between 48 variables which affect the DR, “loan volume” variable has the most effect. These and other factors emphasize the need for SMEs credit scoring in developing countries.
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Globerman, Steven. "Investing abroad and investing at home: complements or substitutes?" Multinational Business Review 20, no. 3 (August 17, 2012): 217–30. http://dx.doi.org/10.1108/15253831211261469.
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PurposeThe purpose of the study is to assess whether outward foreign direct investment (OFDI) and home country capital investment are substitutes or complements.Design/methodology/approachCase studies of 22 Canadian multinational companies (MNCs) were carried out, and the qualitative and quantitative information from the case studies was used to evaluate whether OFDI and home country capital investment were substitutes or complements for the sample MNCs over the period 2000‐2010.FindingsTwo primary strategic motives were identified for the OFDI undertaken by the sample MNCs: market‐seeking; and resource‐seeking. Across the sample, domestic investment was typically a poor strategic alternative to OFDI. Furthermore, OFDI promoted faster revenue growth for the MNCs which stimulated increased domestic investment in later time periods. Hence, OFDI and domestic capital investment are complements in the longer run.Practical implicationsHome country government policies that directly or indirectly discourage OFDI will also discourage domestic investment by home country MNCs. This, in turn, might discourage investment by small and medium‐sized enterprises in the home country, if government limitations on OFDI hamper the growth of MNC head offices in the home country.Originality/valueThe study provides evidence drawing on case studies rather than traditional econometric models. The case study methodology provides evidence on the underlying strategic imperatives for OFDI that is not identified by econometric studies.
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Gurney, Andrew. "Obtaining Estimates for the Standard Errors of Long-Run Parameters." National Institute Economic Review 128 (May 1989): 89–90. http://dx.doi.org/10.1177/002795018912800107.
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Macro Modelling Notes is a new section of the Review, which we hope will appear on a regular basis. It will contain a small number of very short papers that have arisen from applied macro modelling work at the Institute or elsewhere. In the course of building and operating macro models, a large amount of information is used and produced that may never enter the public domain. This may be because the information is not substantial enough to justify a whole journal article, or because it is specific to the practice of using a macro econometric model. However this information is often of general interest to other economists, and is nearly always helpful to other macro modellers. This section is designed as an outlet for information of this kind, which might otherwise not be published in any readily accessible form.The three notes below provide three different examples of this type of note. The first involves econometric practice, and shows how long-run standard errors can be simply derived using standard regression techniques. The second presents some econometric results on export pricing obtained during normal ‘model maintenance’ of our world model GEM. The third considers the problem of setting terminal dates for a consistent expectations model.This new section of the Review is designed as a vehicle for all UK and overseas macro modellers, and therefore outside submissions are strongly encouraged. Submissions must be of about the length of the notes shown here, and contain relevant material that does not form part of a larger article soon to be published. Unlike Review articles, these notes will not normally be refereed, but the Editorial Board may consult expert advice when necessary.
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Chłoń-Domińczak, Agnieszka, Anna Fiedukowicz, and Robert Olszewski. "Geographical and Economic Factors Affecting the Spatial Distribution of Micro, Small, and Medium Enterprises: An Empirical Study of The Kujawsko-Pomorskie Region in Poland." ISPRS International Journal of Geo-Information 9, no. 7 (July 1, 2020): 426. http://dx.doi.org/10.3390/ijgi9070426.
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Micro, small, and medium-sized enterprises (MSMEs) are an essential part of economies at the national, regional, and local levels. Understanding the determinants of the development of this sector is interesting not only for researchers but also for local governments to support the development of this sector. This paper analyses micro, small, and medium enterprises at the gmina (local) level in one region, the Kujawsko-Pomorskie voivodship (NUTS2) in Poland. The authors use multivariate linear regression, spatial econometrics, and classification trees to model the influence of different factors on the number of enterprises relative to population size. The authors found that the most crucial factor in all cases, independently of the method used, is the local government’s revenue from personal income tax per capita. This finding, together with the lack of significance of variables related to the distance to technological parks or economic zones, indicates that the enterprises in the region produce mainly for local consumption and lack innovativeness. The authors also examined the influence of spatial context on the number of enterprises. The most important factor seems to be the percentage of built-up areas, but there are also others, depending on the model type; again, this confirms the local character of the activity of micro, small, and medium enterprises in the region. Variables representing the spatial context can explain the relative number of enterprises with coefficient of determination (R2) between 0.30 and 0.45, which shows that this context played a relatively significant role in the development of the MSME sector in the region. On the other hand, the econometric models (that include the neighborhood) are only significant (improving R2) for medium enterprises, which means that medium enterprises expand their activity beyond the local range.
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Đuričin, Sonja, Isidora Beraha, Olivera Jovanović, Marija Mosurović Ružičić, Marija Lazarević-Moravčević, and Mihailo Paunović. "The Efficiency of National Innovation Policy Programs: The Case of Serbia." Sustainability 14, no. 14 (July 11, 2022): 8483. http://dx.doi.org/10.3390/su14148483.
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We aimed to assess the efficiency of the selected national innovation policy programs in the Republic of Serbia. We analyzed the impact of the Innovation Fund’s Mini-Grants and Matching Grants programs on the operating revenue growth of beneficiary micro, small, and medium enterprises. An econometric analysis of panel data was conducted. Because of the small number of periods observed, a model of individual effects was applied. Conclusions and recommendations were based on the results of random effects models. The findings indicate that program funding increased business revenues compared to the period before and that there was a direct link between indebtedness and revenue growth, which confirmed the positive impact of financing on the sustainable development prospects of beneficiaries through facilitating access to funding and innovation capacity improvement. These findings can have important policy implications as they provide guidelines for designing future actions and empirically confirm the need to increase public expenditures for innovation policy.
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Igityan, Haykaz. "Asymmetric Effects of Monetary Policy on the Armenian Economy." Russian Journal of Money and Finance 80, no. 1 (March 2021): 46–103. http://dx.doi.org/10.31477/rjmf.202101.46.
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Whether inflation and output respond symmetrically or asymmetrically to the same size of contractionary and expansionary monetary policy shock has important policy implications. This paper shows the presence of asymmetric responses in Armenian inflation and output to positive and negative monetary policy shocks of the same size by employing econometric models. Contractionary policy decreases inflation less than expansionary policy increases it. Output reacts in the opposite way. An estimated small open economy DSGE model with sticky wages and investment adjustment costs explains about half of the asymmetry observed in the monetary policy transmission mechanism. This paper finds that the main part of inflation reaction asymmetry is a result of a highly convex Phillips curve for the importers. The nonlinearities of the internal economy explain the predominant part of the asymmetry in output reaction.
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Müller, Sven, and Knut Haase. "Local revenue response to service quality: spatial effects in seasonal ticket revenue data." European Journal of Marketing 49, no. 9/10 (September 14, 2015): 1391–416. http://dx.doi.org/10.1108/ejm-10-2013-0531.
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Purpose – This paper aims to consider spatial effects in the analysis of the relationship of revenue and service quality. When firms’ customers are located in spatially dispersed areas, it can be difficult to manage service quality on a geographically small scale because the relative importance of service quality might vary spatially. Moreover, standard approaches discussed so far in the marketing science literature usually neglect spatial effects, such as spatial dependencies (e.g. spatial autocorrelation) and spatial drift (spatial non-stationarity). Design/methodology/approach – The authors propose a comprehensive but intelligible approach based on spatial econometric methods that cover spatial dependencies and spatial drift simultaneously. In particular, they incorporate the spatial expansion method (spatial drift) into spatial econometric models (e.g. spatial lag model). Findings – Using real company data on seasonal ticket revenue (dependent variable) and service quality (independent variables) of a regional public transport service provider, the authors find that the elasticity for the length of the public transport network is between 0.2 and 0.5, whereas the elasticity for the headway is between −0.2 and 0.6, for example. The authors control for several socio-economic, socio-demographic and land-use variables. Practical implications – Based on the empirical findings, the authors show that addressing spatial effects of service data can improve management’s ability to implement programs aimed at enhancing seasonal ticket revenue. Therefore, they derive a spatial revenue response function that enables managers to identify small-scale areas that are most efficient in terms of increasing revenue by service improvement. Originality/value – The paper addresses the need to account for spatial effects in revenue response functions of public transport companies.
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Afandi, Elvin, and Nazim Habibov. "Social trust and use of banking services across households in 28 transitional countries." International Journal of Social Economics 43, no. 4 (April 11, 2016): 431–43. http://dx.doi.org/10.1108/ijse-10-2014-0204.
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Purpose – The purpose of this paper is to use survey data from a sample of 29,000 households from 28 transitional countries and Turkey to address two main questions: first, is there any effect of social trust on the use of banking services; and second, what are the household-level and country-specific determinants of using banking services in transitional countries. Design/methodology/approach – The authors use binary probit models, instrumental variables methods and various econometric specifications to test the hypothesis. Findings – The authors found that the higher level of trust in people predicts a greater level in use of banking services by households regardless of the model specifications and econometric adjustments employed. This association appears to be more prominent among less educated respondents and in countries with low levels of legal enforcement. The results also suggest that location, income and wealth of households, along with country income level, legal enforcement and inflation rates strongly affect the decisions made by households regarding their use of banking services. In contrast, the authors found either a very small or non-significant impact with regard to bank ownership structure on the use of banking services across households. Originality/value – To the best of the knowledge this is the first study which specifically focusses on social trust and the usage of formal banking services across a large set of transitional countries.
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Rötheli, Tobias. "Heuristics versus econometrics as a basis for forecasting international inflation differentials." foresight 21, no. 2 (April 8, 2019): 216–26. http://dx.doi.org/10.1108/fs-07-2018-0070.
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Purpose This study aims to address the issue of prediction of inflation differences for an economy that considers either fixing its exchange rate or joining a currency union. In this setting, individual countries have limited control over their inflation, and anticipating the possible course of domestic inflation relative to inflation abroad becomes an important input in policy-making. In this context, the author compares simple forecast heuristics and econometric modeling. Design/methodology/approach The study compares two basically different approaches. The first approach of forecasting consists of simple heuristics. Various heuristics are considered that differ with respect to the economic reasoning that goes into quantifying the forecast rules. The simplest such forecasting heuristic suggests that the average over all available observations of inflation differentials should be taken as a predictor for the future. Bringing more economic insight to bear suggests a further heuristic according to which historical inflation differentials should be adjusted for changes in the nominal exchange rate. A further variant of this approach suggests that a forecast should exclusively rely on data from earlier times under a pegged exchange rate. A fundamentally different approach to prediction builds on dynamic econometric models estimated by using all available historical data independent of the currency regime. Findings The author studies three small member countries of the Eurozone, i.e. Finland, Luxembourg and Portugal. For the evaluation of the various forecasting strategies, he performs out-of-sample predictions over a horizon of five years. The comparison of the four different forecasting strategies documents that the variant of the forecast heuristic that draws on data from earlier experiences under fixed exchange rates performs better than the forecast based on the estimated econometric model. Practical implications The findings of this study provide helpful guidelines for countries considering either joining a currency union or fixing their exchange rate. The author shows that a simple forecasting heuristic gives sound advice for assessing the likely course of inflation. Originality/value This study describes how economic theory can guide the selection of historical data for assessing likely future developments. The analysis shows that using a simple heuristic based on historical analogy can lead to better forecasts than the analytically more sophisticated approach of econometric modeling.
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Mathes, Tim, and Oliver Kuss. "Beta-binomial models for meta-analysis with binary outcomes: Variations, extensions, and additional insights from econometrics." Research Methods in Medicine & Health Sciences 2, no. 2 (February 17, 2021): 82–89. http://dx.doi.org/10.1177/2632084321996225.
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Background Meta-analysis of systematically reviewed studies on interventions is the cornerstone of evidence based medicine. In the following, we will introduce the common-beta beta-binomial (BB) model for meta-analysis with binary outcomes and elucidate its equivalence to panel count data models. Methods We present a variation of the standard “common-rho” BB (BBST model) for meta-analysis, namely a “common-beta” BB model. This model has an interesting connection to fixed-effect negative binomial regression models (FE-NegBin) for panel count data. Using this equivalence, it is possible to estimate an extension of the FE-NegBin with an additional multiplicative overdispersion term (RE-NegBin), while preserving a closed form likelihood. An advantage due to the connection to econometric models is, that the models can be easily implemented because “standard” statistical software for panel count data can be used. We illustrate the methods with two real-world example datasets. Furthermore, we show the results of a small-scale simulation study that compares the new models to the BBST. The input parameters of the simulation were informed by actually performed meta-analysis. Results In both example data sets, the NegBin, in particular the RE-NegBin showed a smaller effect and had narrower 95%-confidence intervals. In our simulation study, median bias was negligible for all methods, but the upper quartile for median bias suggested that BBST is most affected by positive bias. Regarding coverage probability, BBST and the RE-NegBin model outperformed the FE-NegBin model. Conclusion For meta-analyses with binary outcomes, the considered common-beta BB models may be valuable extensions to the family of BB models.
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Primierova, Olena, and Juliet Abakumova. "Globalization and Assessement of the Soft Power Potential of Belarus Using Econometric Instruments." SHS Web of Conferences 92 (2021): 08015. http://dx.doi.org/10.1051/shsconf/20219208015.
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Research background: When it comes to conducting international events in a country with a small open economy, the issue of assessing the ratio of costs of the event to subsequent economic effects is relevant. If the evaluation of short-term revenues in the country is quite realistic, then quantifying the long-term effect on a country’s image is much more difficult, and directly related to the concept of soft power and its evaluation as a neutral instrument in international relations. The study was based on the concept of soft power and its instrument, such as the international image of the state, the improvement of which is possible by conducting various events of an international level. Purpose of the article: The opportunity was of interest to assess the effect of using one of the neutral tools of the so-called soft power, such as holding international sports events. Methods: To test hypotheses, time series models were used on the example of Belarus data. Also, for Belarus, the Soft Power Index was calculated according to the methodology of the Moscow School of Management Skolkovo and the British audit and consulting company Ernst and Young. Findings & Value added: The conclusion is confirmed that the holding of sports events of an international scale directly affects the increase in indexing in the search queries of keywords characterizing the country, which in turn through the components of the globalization index positively affects its values for the country. Also, the holding of sports and cultural events has a positive effect on the influx of foreign tourists into the country.
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HAIM, DAVID, RALPH J. ALIG, ANDREW J. PLANTINGA, and BRENT SOHNGEN. "CLIMATE CHANGE AND FUTURE LAND USE IN THE UNITED STATES: AN ECONOMIC APPROACH." Climate Change Economics 02, no. 01 (February 2011): 27–51. http://dx.doi.org/10.1142/s2010007811000218.
Full textAbstract:
An econometric land-use model is used to project regional and national land-use changes in the United States under two IPCC emissions scenarios. The key driver of land-use change in the model is county-level measures of net returns to five major land uses. The net returns are modified for the IPCC scenarios according to assumed trends in population and income and projections from integrated assessment models of agricultural prices and agricultural and forestry yields. For both scenarios, we project large increases in urban land by the middle of the century, while the largest declines are in cropland area. Significant differences among regions in the projected patterns of land-use change are evident, including an expansion of forests in the Mountain and Plains regions with declines elsewhere. Comparisons to projections with no climate change effects on prices and yields reveal relatively small differences. Thus, our findings suggest that future land-use patterns in the U.S. will be shaped largely by urbanization, with climate change having a relatively small influence.