Journal articles on the topic 'Performance standards Econometric models'
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Kim, Dong-sup, and Seungwoo Shin. "THE ECONOMIC EXPLAINABILITY OF MACHINE LEARNING AND STANDARD ECONOMETRIC MODELS-AN APPLICATION TO THE U.S. MORTGAGE DEFAULT RISK." International Journal of Strategic Property Management 25, no. 5 (July 13, 2021): 396–412. http://dx.doi.org/10.3846/ijspm.2021.15129.
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This study aims to bridge the gap between two perspectives of explainability−machine learning and engineering, and economics and standard econometrics−by applying three marginal measurements. The existing real estate literature has primarily used econometric models to analyze the factors that affect the default risk of mortgage loans. However, in this study, we estimate a default risk model using a machine learning-based approach with the help of a U.S. securitized mortgage loan database. Moreover, we compare the economic explainability of the models by calculating the marginal effect and marginal importance of individual risk factors using both econometric and machine learning approaches. Machine learning-based models are quite effective in terms of predictive power; however, the general perception is that they do not efficiently explain the causal relationships within them. This study utilizes the concepts of marginal effects and marginal importance to compare the explanatory power of individual input variables in various models. This can simultaneously help improve the explainability of machine learning techniques and enhance the performance of standard econometric methods.
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Andersen, Torben G. "SIMULATION-BASED ECONOMETRIC METHODS." Econometric Theory 16, no. 1 (February 2000): 131–38. http://dx.doi.org/10.1017/s0266466600001080.
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The accessibility of high-performance computing power has always influenced theoretical and applied econometrics. Gouriéroux and Monfort begin their recent offering, Simulation-Based Econometric Methods, with a stylized three-stage classification of the history of statistical econometrics. In the first stage, lasting through the 1960's, models and estimation methods were designed to produce closed-form expressions for the estimators. This spurred thorough investigation of the standard linear model, linear simultaneous equations with the associated instrumental variable techniques, and maximum likelihood estimation within the exponential family. During the 1970's and 1980's the development of powerful numerical optimization routines led to the exploration of procedures without closed-form solutions for the estimators. During this period the general theory of nonlinear statistical inference was developed, and nonlinear micro models such as limited dependent variable models and nonlinear time series models, e.g., ARCH, were explored. The associated estimation principles included maximum likelihood (beyond the exponential family), pseudo-maximum likelihood, nonlinear least squares, and generalized method of moments. Finally, the third stage considers problems without a tractable analytic criterion function. Such problems almost invariably arise from the need to evaluate high-dimensional integrals. The idea is to circumvent the associated numerical problems by a simulation-based approach. The main requirement is therefore that the model may be simulated given the parameters and the exogenous variables. The approach delivers simulated counterparts to standard estimation procedures and has inspired the development of entirely new procedures based on the principle of indirect inference.
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Ferro, Gustavo, and Carlos A. Romero. "Setting performance standards for regulation of water services: Benchmarking Latin American utilities." Water Policy 13, no. 5 (April 23, 2011): 607–23. http://dx.doi.org/10.2166/wp.2011.042.
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The aim of this study is to estimate both stochastic and mathematical programming efficiency cost frontiers for the Latin American water sector, by means of econometric and Data Envelopment Analysis techniques, using the ADERASA database. ADERASA is the Latin American association for water regulators, which has made a systematic job of data collection, among other initiatives. This study fills a gap in the understanding of relative efficiency in the Latin American water sector, using a consistent database. First, we present a survey of the empirical literature related to cost and production frontiers in the water and sanitation sector. Second, once alternative specifications were chosen, models have been estimated and environmental variables included in an exploratory way. The coefficients have the expected signs and plausible values. Some consistency between methodologies is found. This paper yields two results. The better knowledge of the underlying cost (or production) model is a first step to using benchmarking as a regulatory tool. The policy implications are relatively straightforward. With benchmarking technology it is possible to coordinate the action of different regulators, each with their own asymmetry of information. The key is setting indicative standards which constitute the basis of further discussion.
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Garrido, Rodrigo A., and Hani S. Mahmassani. "Forecasting Short-Term Freight Transportation Demand: Poisson STARMA Model." Transportation Research Record: Journal of the Transportation Research Board 1645, no. 1 (January 1998): 8–16. http://dx.doi.org/10.3141/1645-02.
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A framework for analyzing, describing, and forecasting freight flows for operational and tactical purposes is presented. A dynamic econometric model is proposed. This model incorporates the spatial and temporal characteristics of freight demand within a stochastic framework. The model was applied in an actual context and its performance was compared with standard time series models (benchmark) for forecasting ability. The proposed model outperformed the benchmark from the econometric viewpoint. Extensive diagnostic checking and sensitivity analysis confirmed the robustness of the modeling methodology for short-term forecasting applications.
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Wu, Kejin, and Sayar Karmakar. "Model-Free Time-Aggregated Predictions for Econometric Datasets." Forecasting 3, no. 4 (December 8, 2021): 920–33. http://dx.doi.org/10.3390/forecast3040055.
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Forecasting volatility from econometric datasets is a crucial task in finance. To acquire meaningful volatility predictions, various methods were built upon GARCH-type models, but these classical techniques suffer from instability of short and volatile data. Recently, a novel existing normalizing and variance-stabilizing (NoVaS) method for predicting squared log-returns of financial data was proposed. This model-free method has been shown to possess more accurate and stable prediction performance than GARCH-type methods. However, whether this method can sustain this high performance for long-term prediction is still in doubt. In this article, we firstly explore the robustness of the existing NoVaS method for long-term time-aggregated predictions. Then, we develop a more parsimonious variant of the existing method. With systematic justification and extensive data analysis, our new method shows better performance than current NoVaS and standard GARCH(1,1) methods on both short- and long-term time-aggregated predictions. The success of our new method is remarkable since efficient predictions with short and volatile data always carry great importance. Additionally, this article opens potential avenues where one can design a model-free prediction structure to meet specific needs.
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Cadotte, Ernest R., Robert B. Woodruff, and Roger L. Jenkins. "Expectations and Norms in Models of Consumer Satisfaction." Journal of Marketing Research 24, no. 3 (August 1987): 305–14. http://dx.doi.org/10.1177/002224378702400307.
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Disconfirmation models of customer satisfaction employing three alternative standards of performance were compared by using causal modeling. Pre- and post-measures were obtained from subjects in three different use situations. The disconfirmation paradigm is supported. The analysis suggests that best brand norm and product norm are additional standards used for evaluating focal brand performance.
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G. C., Surya Bahadur, and Ravindra Prasad Baral. "The Effect of Corporate Governance and Ownership Structure on Financial Performance of Listed Companies in Nepal." Journal of Nepalese Business Studies 12, no. 1 (December 31, 2019): 1–18. http://dx.doi.org/10.3126/jnbs.v12i1.28148.
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The paper attempts to analyze relationships among corporate governance, ownership structure and firm performance in Nepal. The study comprises of panel data set of 25 firms listed at Nepal Stock Exchange (NEPSE) covering a period of five years from 2012 to 2016. The econometric methodology for the study consists primarily of least squares dummy variable (LSDV) model, fixed and random effects panel data models and two-stage least squares (2SLS) model. The study finds bi-directional relationship between corporate governance and performance. Among corporate governance internal mechanisms; smaller board size, higher proportion of independent directors, reducing ownership concentration, improving standards of transparency and disclosure, and designing appropriate director compensation package are important dimensions that listed firms and regulators in Nepal should focus on. Ownership concentration is found to have positive effect on performance; however, it affects corporate governance negatively. This study raises understanding and provides empirical evidence for endogenous relationship between corporate governance and performance and offers support for principal-principal agency relationship. The results of this study lead to several practical implications for listed firms as well as policymakers of Nepal in promoting sound corporate governance practices and codes. For listed companies, the improvement in compliance with a code of corporate governance or voluntary adoption of best practices can provide a means of achieving improved performance.
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Ahmed, Elsadig Musa. "Modelling green productivity spillover effects on sustainability." World Journal of Science, Technology and Sustainable Development 17, no. 3 (April 1, 2020): 257–67. http://dx.doi.org/10.1108/wjstsd-01-2020-0009.
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PurposeThis study aims to explain the integration of innovation and climate with the economic growth Green Productivity (GP) concept. This is drawn from the integration of two important developmental strategies: productivity improvement and environmental protection. Productivity provides the framework for continuous improvement, while environmental protection provides the foundation for sustainable development. Therefore, GP is a strategy for enhancing productivity and environmental performance for overall socio-economic development.Design/methodology/approachThree variations of frameworks and econometric model were developed to measure green total factor productivity, green labour productivity and green capital productivity, and their contributions to green productivity and sustainable development; these were based on extensive and intensive growth theories.FindingsThe sustainability of higher economic growth will likely continue to be productivity driven. This will be through the enhancement of total factor productivity (TFP) as technological progress in nations that combined the three dimensions of sustainable development (economic development, environmental protection and social sustainable development via human capital development). Such an enhancement needs to emphasise the quality of the workforce, demand intensity, economic restructuring, capital structure, technical progress and environmental standards. It should be recalled that green productivity through green TFP demonstrates the sustainable development concept of progressing technologically. It will ensure the rights of the future, as well as current, generations for them to enjoy a better life.Originality/valueThe study fills the gaps in growth theories by developing three variations of frameworks and econometric models, and internalising pollutants emissions as private and unpriced inputs in the three models. Further, the green capital productivity model is the sole contributing model developed in this research; it has not been thought about in any previous studies. This study highlighted the green productivity that is ignored by the studies that have been awarded the Nobel Prize in economic sciences in 2018.
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Tse, David K., and Peter C. Wilton. "Models of Consumer Satisfaction Formation: An Extension." Journal of Marketing Research 25, no. 2 (May 1988): 204–12. http://dx.doi.org/10.1177/002224378802500209.
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The authors extend consumer satisfaction literature by theoretically and empirically (1) examining the effect of perceived performance using a model first proposed by Churchill and Surprenant, (2) investigating how alternative conceptualizations of comparison standards and disconfirmation capture the satisfaction formation process, and (3) exploring possible multiple comparison processes in satisfaction formation. Results of a laboratory experiment suggest that perceived performance exerts direct significant influence on satisfaction in addition to those influences from expected performance and subjective disconfirmation. Expectation and subjective disconfirmation seem to be the best conceptualizations in capturing satisfaction formation. The results suggest multiple comparison processes in satisfaction formation.
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Mazreku, Ibish, Fisnik Morina, and Elvis Curraj. "Evaluation of the Financial Performance of Pension Funds. Empirical Evidence: Kosovo, Albania and North Macedonia." European Journal of Sustainable Development 9, no. 1 (February 1, 2020): 161. http://dx.doi.org/10.14207/ejsd.2020.v9n1p161.
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Purpose: This research paper aims to analyze the evaluation of the financial performance of pension funds, to find the relationship between contributions, return on investment and net asset value with pension fund performance. The following research questions have been asked in order to realize the purpose of the research: What are the factors affecting the performance of the pension fund? What is the relationship between pension fund performance and contributions, return on investment, and net asset value?
Methodology: For the specification of the econometric model of this study, we rely on secondary data published in official World Bank reports and reports of pension funds in Kosovo, Albania and North Macedonia. To measure the empirical results, these statistical tests are used: standard multiple regression, fixed effects model, random effect model, and Hausman Taylor Regression.
Findings: Based on the empirical results, we can conclude that the increase in gross domestic product, return on investment, contributions and net assets have positively influenced the performance of pension funds for the countries included in the study. The other independent variable, the exchange rate, on the basis of econometric estimations, has turned out to be non-significant.
Practical implications: The empirical results of this study may recommend that relevant institutions in Kosovo, Albania and North Macedonia undertake reforms towards the creation of efficient pension systems, and these reforms are of crucial importance for pension systems, which have an economic and social character in their function as fund accumulators and benefit distributors for the categories in need.
Originality: The study is conducted with secondary data and all the empirical analysis are original based on the authors' calculations through econometric models. Through the results of this study we aim to provide additional empirical evidence on the performance of pension funds in Kosovo, Albania and North Macedonia, recommending that relevant institutions improve the functioning of the pension system, as it is a very important part of a financial system of a country which has an impact on economic growth.
Keywords: financial performance, pension fund, contributions, net assets, return on investment
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ZAVHORODNIA, TETIANA, OKSANA PROSKUROVYCH, and KATERYNA GORBATIUK. "DIAGNOSIS OF THE RESULT OF A SEWING ENTERPRISE PRODUCTION ACTIVITY." MODELING THE DEVELOPMENT OF THE ECONOMIC SYSTEMS 1, no. 1 (June 2021): 47–54. http://dx.doi.org/10.31891/mdes/2021-1-6.
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In the scientific article, the process of diagnosing the production activity result of a sewing enterprise is investigated. An assessment of the state of production and marketing activities of a sewing enterprise based on the dynamics of the volume of marketable and sold products. The factor analysis of the efficiency of resources using (number of human resources, cost of materials and fixed assets) on an enterprise of sewing branch is carried out. Econometric modeling and forecasting of the production activity results, concerning the change of the basic components of resource potential of a sewing enterprise, are applied. Several econometric and one trend models, which describe the change of the volume of marketable products on a sewing factory, have been built. In addition to linear dependences, the power and multiplicative production function of changing the production activity result is formed. All constructed models have a high value of the coefficient of determination, which indicates a significant share of the influence of selected factors on the performance indicator. At the same time, they are adequate, so they can be used for forecasting the volume of marketable products. The results of modeling and further forecasting proved that the best models are the three-factor model, power model, two-factor model built on the impact of staff and cost of material resources, and one-factor relationship between product volume and cost of materials. These models have a sufficiently high value of the coefficient of determination, the lowest value of the standard error, and the adequacy of these models according to Fisher's criterion and the reliability of their parameters according to Student's criterion.
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Koki, Constandina, Stefanos Leonardos, and Georgios Piliouras. "Do Cryptocurrency Prices Camouflage Latent Economic Effects? A Bayesian Hidden Markov Approach." Future Internet 12, no. 3 (March 21, 2020): 59. http://dx.doi.org/10.3390/fi12030059.
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We study the Bitcoin and Ether price series under a financial perspective. Specifically, we use two econometric models to perform a two-layer analysis to study the correlation and prediction of Bitcoin and Ether price series with traditional assets. In the first part of this study, we model the probability of positive returns via a Bayesian logistic model. Even though the fitting performance of the logistic model is poor, we find that traditional assets can explain some of the variability of the price returns. Along with the fact that standard models fail to capture the statistic and econometric attributes—such as extreme variability and heteroskedasticity—of cryptocurrencies, this motivates us to apply a novel Non-Homogeneous Hidden Markov model to these series. In particular, we model Bitcoin and Ether prices via the non-homogeneous Pólya-Gamma Hidden Markov (NHPG) model, since it has been shown that it outperforms its counterparts in conventional financial data. The transition probabilities of the underlying hidden process are modeled via a logistic link whereas the observed series follow a mixture of normal regressions conditionally on the hidden process. Our results show that the NHPG algorithm has good in-sample performance and captures the heteroskedasticity of both series. It identifies frequent changes between the two states of the underlying Markov process. In what constitutes the most important implication of our study, we show that there exist linear correlations between the covariates and the ETH and BTC series. However, only the ETH series are affected non-linearly by a subset of the accounted covariates. Finally, we conclude that the large number of significant predictors along with the weak degree of predictability performance of the algorithm back up earlier findings that cryptocurrencies are unlike any other financial assets and predicting the cryptocurrency price series is still a challenging task. These findings can be useful to investors, policy makers, traders for portfolio allocation, risk management and trading strategies.
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Agyeman, A. "Estimating the Returns to Schooling: A Comparison of Fixed Effects and Selection Effects Models for Twins." Ghana Journal of Science 61, no. 1 (July 31, 2020): 15–30. http://dx.doi.org/10.4314/gjs.v61i1.2.
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Strong empirical links exist between the number of years spent schooling and earnings. However, the relationship may be masked due to the effect of unobserved factors that influence both wages and schooling. Two of the main econometric models, namely fixed-effects and selection-effects, used to analyse returns to schooling were compared using monozygotic and dizygotic twins’ datasets in Ghana. The efficiency of the models was assessed based on the standard errors associated with the return to schooling estimates. Goodness of fit measures was used as a basis for comparison of the performance of the two models. The results revealed that based on their standard errors, the regression estimates from the selection effects model (MZ = 0.1014±0.0197; DZ = 0.0947±0.0095) were more efficient than the regression estimates from the fixed-effects model (MZ = 0.1115±0.0353; DZ = 0.082±0.0127). However, the AICc values of the fixed effects model (MZAICc = 57.8 and DZAICc = 105.4) were smaller than the AICc values of the selection effects model (MZAICc = 151.6 and DZAICc = 221.6). Findings from the study indicate that, although both models produced consistent estimates of the economic returns to schooling, the fixed effects model provided a better fit to the twins’ data set.
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Sánchez-Ollero, José Luis, Alejandro García-Pozo, and Macarena Marchante-Lara. "Measuring the effects of quality certification on labour productivity." International Journal of Contemporary Hospitality Management 27, no. 6 (August 10, 2015): 1100–1116. http://dx.doi.org/10.1108/ijchm-02-2014-0057.
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Purpose – The purpose of this study was to evaluate the impact of quality certifications on apparent labour productivity in a sample of hotels in Spain. Design/methodology/approach – In line with Mairesse and Kremp (1993), the theoretical model was based on a Cobb–Douglas production function readapted to the goals of the study. Findings – The descriptive results show that labour productivity increases only when certifications and quality standards specific to the hospitality industry are implemented and the tourist destination is committed to quality. The econometric analysis shows that the hotel category, belonging to a chain, and outsourcing services have a positive impact on labour productivity. In contrast, the location of the establishment in areas other than the coast or the capital city of a province has a negative effect on labour productivity. Of the quality models and certifications studied, only the Spanish Q-Mark certificate significantly improves hotel productivity (an average increase of 23.27 per cent). Practical implications – These results provide support for the Spanish Tourism Quality System implemented by the Spanish Ministry of Tourism, which has not only attempted to increase the quality of tourism hotels by increasing their competitiveness and performance but also by providing them with a quality certificate that can be used as a marketing strategy in international markets. Originality/value – The main contribution of this study is to show how the adoption of quality standards and certifications increases or decreases labour productivity in hotels. Given that most of the previous literature has only taken into account quantities, this study adds to the literature by incorporating the concept of quality into productivity issues.
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Qiu, Buhui, and Steve L. Slezak. "The Equilibrium Relationships between Performance-Based Pay, Performance, and the Commission and Detection of Fraudulent Misreporting." Accounting Review 94, no. 2 (July 1, 2018): 325–56. http://dx.doi.org/10.2308/accr-52207.
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ABSTRACT We develop an agency model in which managerial information manipulation creates pooling and entails ex post costs internal and/or external to the firm. We examine the implications of the strategic interactions between shareholders (who set internal governance and managerial incentive compensation), the manager (who exerts effort and reports on its outcome), and an external regulatory authority or RA (who investigates for fraud and levies penalties ex post). When the RA cannot pre-commit to an ex post investigation strategy, a fraudulent equilibrium obtains if the firm's internal governance costs are sufficiently high. Consistent with (so far fairly scant) post-SOX empirical evidence, but the opposite of the implications of signal-jamming models and equilibria with pre-commitment, the model implies an increase in minimum internal governance standards or ex post fraud penalties (as with SOX) results in decreased equilibrium pay-for-performance sensitivity and firm performance.
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Tassey, Gregory. "Competing in Advanced Manufacturing: The Need for Improved Growth Models and Policies." Journal of Economic Perspectives 28, no. 1 (February 1, 2014): 27–48. http://dx.doi.org/10.1257/jep.28.1.27.
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The United States has underinvested for several decades in a set of productivity-enhancing assets necessary for the long-term health of its manufacturing sector. Conventional characterizations of the process of bringing new advanced manufacturing products to market usually leave out two important elements: One is “proof-of-concept research” to establish broad “technology platforms” that can then be used as a basis for developing actual products. The second is a technical infrastructure of “infratechnologies” that include the analytical tools and standards needed for measuring and classifying the components of the new technology; metrics and methods for determining the adequacy of the multiple performance attributes of the technology; and the interfaces among hardware and software components that must work together for a complex product to perform as specified. If the public–private dynamics are not properly aligned to encourage proof-of-concept research and needed infratechnologies, then promising advances in basic science can easily fall into a “valley of death” and fail to evolve into modern advanced manufacturing technologies that are ready for the marketplace. Each major technology has a degree of uniqueness that demands government support sufficiently sophisticated to allow efficient adaptation to the needs of its particular industry, whether semiconductors, pharmaceuticals, computers, communications equipment, medical equipment, or some other technology-based industry.
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Koki, Constandina, Stefanos Leonardos, and Georgios Piliouras. "Do Cryptocurrency Prices Camouflage Latent Economic Effects? A Bayesian Hidden Markov Approach." Proceedings 28, no. 1 (October 21, 2019): 5. http://dx.doi.org/10.3390/proceedings2019028005.
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With Bitcoin, Ether and more than 2000 cryptocurrencies already forming a multi-billion dollar market, a proper understanding of their statistical and financial properties still remains elusive. Traditional economic theories do not explain their characteristics and standard financial models fail to capture their statistic and econometric attributes such as their extreme variability and heteroskedasticity. Motivated by these findings, we study Bitcoin and Ether prices via a Non-Homogeneous Pólya Gamma Hidden Markov (NHPG) model that has been shown to outperform its counterparts in conventional financial data. The NHPG algorithm has good in-sample performance and identifies both linear and non-linear effects of the predictors. Our results indicate that all price series are heteroskedastic with frequent changes between the two states of the underlying Markov process. In a somewhat unexpected result, the Bitcoin and Ether prices, although correlated, are significantly affected by different variables. We compare long term to short term Bitcoin data and find that significant covariates may change over time. Limitations of the current approach—as expressed by the large number of significant predictors and the poor out-of-sample predictions—back earlier findings that cryptocurrencies are unlike any other financial asset and hence, that their understanding requires novel tools and ideas.
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Ashbaugh, Hollis, and Per Olsson. "An Exploratory Study of the Valuation Properties of Cross-Listed Firms' IAS and U.S. GAAP Earnings and Book Values." Accounting Review 77, no. 1 (January 1, 2002): 107–26. http://dx.doi.org/10.2308/accr.2002.77.1.107.
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Despite the increasing integration of global capital markets, there is little evidence on the valuation properties of cross-listed, non-U.S. firms' accounting variables. We use the relative performance of the earnings capitalization, the book value, and the residual income valuation models to explore the valuation properties of International Accounting Standards and U.S. Generally Accepted Accounting Principles earnings and book values reported by non-U.S., cross-listed firms trading in a common equity market. Using non-U.S./non-U.K. firms whose shares trade on the International Stock Exchange Automated Quotation system in London, we find that the earnings capitalization model is the dominant accounting-based valuation model when crosslisted firms report under International Accounting Standards. In contrast, we find that when cross-listed firms report under U.S. Generally Accepted Accounting Principles, the residual income model is the dominant accountingbased valuation model. Our exploratory study provides insights into the valuation implications of allowing a dual reporting system for foreign registrants trading in a common equity market.
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Katchova, Ani L., and Robert Dinterman. "Evaluating financial stress and performance of beginning farmers during the agricultural downturn." Agricultural Finance Review 78, no. 4 (August 6, 2018): 457–69. http://dx.doi.org/10.1108/afr-08-2017-0074.
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Purpose The purpose of this paper is to examine the financial performance and stress of beginning farmers in the USA with emphasis on the agricultural downturn experienced since 2013. Design/methodology/approach Using the US Department of Agriculture’s Agricultural Resource Management Survey (ARMS) data, probit models are estimated to study the personal and farm characteristics that affect whether or not the financial ratios fall into critical zones as defined by the Farm Financial Standards Council. The financial ratios involve liquidity, solvency, profitability, efficiency, and repayment capacity. Findings Beginning farmers are at a greater risk of financial stress on average, with higher likelihood of financial stress in liquidity and efficiency. Further, the recent agricultural downturn has negatively affected liquidity, solvency, and profitability for farmers while repayment capacity does not appear to be affected. During the downturn, beginning farmers are better positioned than the general farming population with respect to liquidity and repayment capacity. Originality/value This paper applies current lending practices to a nationally representative sample of farms over a time of changing economic conditions for the agricultural sector.
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Wendling, Zachary A., David C. Warren, Barry M. Rubin, Sanya Carley, and Kenneth R. Richards. "A Scalable Energy–Economy Model for State-Level Policy Analysis Applied to a Demand-Side Management Program." Economic Development Quarterly 34, no. 4 (July 10, 2020): 372–86. http://dx.doi.org/10.1177/0891242420937792.
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Over the past two decades, states and cities implemented low-carbon energy development, renewable portfolio standards, demand-side management (DSM), renewable energy production incentives, green building requirements, regional carbon trading agreements, and other energy-based economic development initiatives. Yet the dearth of state-level and substate-level models makes it difficult to predict the effects of such actions. This article addresses this shortcoming by presenting the performance results of the new Indiana Scalable Economy and Energy Model (IN-SEEM)—a model utilizing a dynamic, simultaneous equations framework—and demonstrates the model’s capabilities with an analysis of electricity price increases from a DSM program in the state of Indiana. Overall performance of the model is strong, with high adjusted R2 values and low mean absolute percent errors for most of 30 endogenous variables. A DSM price increase analysis finds variation in impact across the state’s 10 major economic sectors and small changes in energy consumption.
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Mwambuli, Erick Lusekelo. "Does Corporate Capital Structure influence Corporate Financial Performance in Developing Economies? Evidence from East African Stock Markets." International Finance and Banking 3, no. 1 (May 10, 2016): 97. http://dx.doi.org/10.5296/ifb.v3i1.9357.
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This paper examines the statistically significant influence which capital structure has had on corporate financial performance of listed non-financial companies in East African stock markets. It used panel data of 272 observations including 34 East African non-financial listed firms listed in East African stock markets such as Dar Es Salaam Stock Market (DSE), Nairobi Securities Exchange (NSE) and Uganda Securities Exchange (USE) for a period of 8 years {i.e. 2006-2013}.Using the Panel Corrected Standard Errors (PCSEs) and Fixed Effect (FE),the study formulated two (2) econometric models with return on assets (ROA) and return on equity (ROE) as dependent variables and measures of corporate financial performance respectively, three (3) independent variables such as short term debt ratio (STDR),long term debt ratio (LTDR) and total debt ratio (TDR) as a measure of capital structure, furthermore the study used size of the firm (SIZ) as a control variable in order to control the differences in firm’s operating environment. The result indicate that capital structure has a negative and statistically significant influence on East African listed firm’s financial performance at 5% significance level. These results show that in average profitable listed firms in East African prefers to use internal source of financing in their capital structure as compared to external source of financing {like Debts-STDR,LTDR and TDR} and this results are supporting pecking order theory. Lastly the study recommends to corporate financial managers of East African non-financial listed firms should reduce financing their operations and growth by debt (STDR,LTDR and TDR) on their capital structure in order to enhance their corporate financial performance, regulatory authorities in East African region such as East African member states securities regulatory authority (EASRA) to formulate policies that will improving of financial markets in the region in order to reduce the cost of debt, further research could examine the influence {if any} of capital structure on sector wise (as per industry-like Manufacturing firms) for East African non-financial listed firms, take into account more control variables which are likely to influence financial performance such as macroeconomic variables (like gross domestic product - GDP) and consider other capital structure theories like ,market timing theory, agency theory which were not considered in our study.
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Nelson, Charles R., and Lawrence R. Klein. "Comparative Performance of U.S. Econometric Models." Journal of the American Statistical Association 87, no. 419 (September 1992): 905. http://dx.doi.org/10.2307/2290243.
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Stekler, H. O. "Comparative performance of U.S. econometric models." International Journal of Forecasting 7, no. 4 (March 1992): 539–40. http://dx.doi.org/10.1016/0169-2070(92)90042-8.
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Alidarous, Manal, and Fouad Jamaani. "The Concurrent Effects of IFRS Mandate and Formal Institutional Quality on the Aftermarket Performance of IPO Firms in Emerging Countries." International Journal of Financial Research 12, no. 3 (January 11, 2021): 320. http://dx.doi.org/10.5430/ijfr.v12n3p320.
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This paper provides the first empirical investigation seeking to find whether International Financial Reporting Standards (IFRS) mandate, changes in the quality of formal institutions, or, the concurrent effect of these two elements can explain the ongoing phenomenon of the aftermarket performance difference of Initial Public Offerings (IPO) firms. We perceive little awareness of the concurrent effect of IFRS mandate and the quality of formal institutions in emerging countries, although these nations account for more than half of the IFRS mandating countries. We employ numerous Difference-in-Differences (DiD) models utilizing reliable IPO and formal institutional data for Saudi Arabia from 2005 to 2017. Our empirical results show that the absence of IFRS influence in the aftermarket performance of IPO firms led us to posit that the quality of formal institutions is the key player in influencing long-term performance of IPO firms in Saudi Arabia. We uncover evidence showing that an improvement in formal institutional quality increases the long-term performance of IPO firms. We find no evidence of a concurrent effect of changes in formal institutional quality and IFRS mandate on the aftermarket performance of IPO firms. Our results show that what does really matter in relation to the aftermarket performance of IPO firms in Saudi Arabia, are the enhancements in the level of formal institutional quality. Our results provide some important implications for IFRS-IPO research.
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Su, Zhan, and Jianmin Tang. "Product innovation, cost-cutting and firm economic performance in the post-crisis context: Canadian micro evidence." Journal of Centrum Cathedra 9, no. 1 (September 2, 2016): 4–26. http://dx.doi.org/10.1108/jcc-08-2016-0009.
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Purpose It has been suggested that to be successful in the current global economy with increased competition and ever changing markets, especially in the post-crisis context, firms need to focus more on innovation in exploring new ideas and designing new products to develop new markets than on cost-cutting strategies to maintain cost leadership in old markets. However, because of the lack of micro data, this conjecture has not been systematically evaluated. This paper aims to fill this important void by studying the economic performance associated with these two different business strategies using Canadian micro data. Design/methodology/approach The main data for our analysis are from the Survey of Innovation and Business Strategy (2009 and 2012) which is a sample-based survey of Canadian government. The authors used in this research regression models for the econometric analysis of the underlying factors for undertaking certain business strategies and how business strategies link to economic performance. They also used propensity score matching to ensure the group of firms with innovation strategy being comparable to that with cost-cutting. Findings The research shows that firms focusing on product innovation are indeed more productive than firms focusing on cost-cutting, although there is no evidence that these two different strategies make a difference in profitability. The first indication from the research has been that certain characteristics of Canadian firms are very useful predictors for firms to undertake product innovation. They are, among other things, the age of the firms, the single-establishment structure of the business and being multinationals. Research limitations/implications This empirical research opens up many interesting avenues for future research. Some other variables could be integrated into the models to increase the rate of explained variance. Moreover, because this research is based only on the case of Canadian firms and for a relatively short period of four years after the 2008 crisis, an extension to other context and to a longer period of time should be interesting. Practical implications The research has confirmed that Canadian firms adopting long-term business strategies based on product innovation are more productive. Social implications The results truly concur with the vision of the Government of Canada, like some other developed countries, on the importance of innovation and its policies in encouraging business innovation in driving the growth of the Canadian economy and improving the standard of living of country. Originality/value Mainly because of the lack of micro data, the existing researches have not provided solid evidence on why firms are choosing different business strategies when they are operating in the same business conditions and how the financial crisis has affected the undertaking of business strategies. They have not established a clear linkage between economic performance and different business strategies, although there has been some anecdotal evidence about their association. This study aims to bridge the knowledge gaps with theoretical and practical contributions.
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Boero, Gianna, and Lawrence R. Klein. "Comparative Performance of U. S. Econometric Models." Economic Journal 102, no. 414 (September 1992): 1264. http://dx.doi.org/10.2307/2234398.
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Oulton, Nicholas. "Do UK Price Indexes Overstate Inflation?" National Institute Economic Review 152 (May 1995): 60–75. http://dx.doi.org/10.1177/002795019515200105.
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Official price indexes may overstate (or understate) inflation for a number of reasons. These include substitution bias, outlet bias, failure to allow properly for quality change, and failure to allow for new goods. This note finds that substitution and outlet bias are probably not significant sources of error in the UK. The other two sources most probably do lead to significant overstatement, but the size of the upward bias cannot at the moment be quantified.‘Since, with technological advance, the quality of products tends to improve, the estimates of consumers' expenditure tend to understate the true growth in standards of consumption’. (CSO a 985, p. 72).‘The Producer Price Indices … make some allowance for changes in models and specifications when these can be identified in terms of changes of cost or in technical performance…. [Allowances for quality change] are necessarily somewhat rough and seldom fully satisfactory’. (CSO 1985, p. 40, emphasis added).
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Lam, Joanna, and Rui Guo. "Investor Obligations in Special Economic Zones: Legal Status, Typology, and Functional Analysis." Journal of International Economic Law 24, no. 2 (April 16, 2021): 321–40. http://dx.doi.org/10.1093/jiel/jgab011.
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ABSTRACT The article discusses various types of investor obligations in special economic zones and examines how they are utilized as instruments for devising development policies. It presents the evolution of regulatory models and practices related to investor obligations in the context of the unilateral character of the legal framework of the zones. The article distinguishes between two types of investor obligations. The first includes commitments focused on quantifiable aspects of economic performance of the investor in the host country, such as the maintenance of a pre-determined level of investment or the creation of a specific number of jobs. The second category of investor obligations is those containing qualitative goals that contribute to the host country’s developmental objectives, such as workforce welfare commitments, environmental standards, and technology transfers. Case studies of Shenzhen, Poland, and Tanzania are analysed to demonstrate how relevant regulatory practices have evolved over time. The case studies are drawn from three different phases of the global proliferation of special economic zones and reflect the regional diversity of the zones.
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Cepeda Cuervo, Edilberto, and Jorge Armando Sicacha. "Spatial Econometric Models: A Bayesian Approach." Revista Colombiana de Estadística 45, no. 2 (July 14, 2022): 341–61. http://dx.doi.org/10.15446/rce.v45n2.92390.
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In this paper we propose Bayesian methods to fit econometric regression models, including those where the variability is assumed to follow a regression structure. We formulate the main functions of the statistical R-package BSPADATA, developed according to the proposed methods to obtain posteriori parameter inferences. After that, we include results of simulated studies to illustrate the use of this package and the performance of the proposed methods. Finally, we provide studies to illustrate the applications of the models and compare our results with that obtained by maximum likelihood.
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Chong, James. "The Statistical Performance of Econometric and Implied Forecasting Models." Journal of Interdisciplinary Economics 15, no. 1 (January 2004): 83–98. http://dx.doi.org/10.1177/02601079x04001500106.
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Krishnamoorthy, Ganesh. "A Multistage Approach to External Auditors' Evaluation of the Internal Audit Function." AUDITING: A Journal of Practice & Theory 21, no. 1 (March 1, 2002): 95–121. http://dx.doi.org/10.2308/aud.2002.21.1.95.
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External auditors are continually facing intense pressure to be more efficient in conducting audits without compromising quality and effectiveness. Optimal utilization of internal audit work can improve both the efficiency and the effectiveness of external audits and can enhance the value of internal auditors to the client organization. The objective of this study is to understand how the three factors (objectivity, work performance, and competence of the internal auditors) identified by auditing standards and by prior research interact in determining the strength of the internal audit function. Most prior studies have attempted to understand external auditors' rank ordering of the importance of the three factors, without an explicit attempt to model the interactions among the factors. The results from these studies are mixed and inconclusive. Hence, prior studies have not produced a consensus about how external auditors seem to weight and combine these factors in order to make assessments relating to the strength of the internal audit function. This study employs analytical methods based on Bayesian probability to model external auditors' evaluation of the internal audit function. Specifically, models based on multistage (cascaded) inference theory are developed and analyzed using numerical sensitivity analysis. The modeling contribution is significant in the sense that it is the only study that provides a theoretical model for the decision process. Results reveal that the importance of the three factors varies with the type of evidence (convergent or conflicting) observed and is contingent on the interrelationships among the three factors. A major conclusion of this study is that in the Bayesian context, it is futile to attempt a ranking of the factors since no single factor will dominate under all conditions. The study also provides avenues for future research and for improving the guidance provided by professional auditing standards that relate to the evaluation of internal audit work.
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Pérez-Pons, María E., Javier Parra-Dominguez, Sigeru Omatu, Enrique Herrera-Viedma, and Juan Manuel Corchado. "Machine Learning and Traditional Econometric Models: A Systematic Mapping Study." Journal of Artificial Intelligence and Soft Computing Research 12, no. 2 (April 1, 2021): 79–100. http://dx.doi.org/10.2478/jaiscr-2022-0006.
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Abstract Context: Machine Learning (ML) is a disruptive concept that has given rise to and generated interest in different applications in many fields of study. The purpose of Machine Learning is to solve real-life problems by automatically learning and improving from experience without being explicitly programmed for a specific problem, but for a generic type of problem. This article approaches the different applications of ML in a series of econometric methods. Objective: The objective of this research is to identify the latest applications and do a comparative study of the performance of econometric and ML models. The study aimed to find empirical evidence for the performance of ML algorithms being superior to traditional econometric models. The Methodology of systematic mapping of literature has been followed to carry out this research, according to the guidelines established by [39], and [58] that facilitate the identification of studies published about this subject. Results: The results show, that in most cases ML outperforms econometric models, while in other cases the best performance has been achieved by combining traditional methods and ML applications. Conclusion: inclusion and exclusions criteria have been applied and 52 articles closely related articles have been reviewed. The conclusion drawn from this research is that it is a field that is growing, which is something that is well known nowadays and that there is no certainty as to the performance of ML being always superior to that of econometric models.
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Shen, Ze, Qing Wan, and David J. Leatham. "Bitcoin Return Volatility Forecasting: A Comparative Study between GARCH and RNN." Journal of Risk and Financial Management 14, no. 7 (July 20, 2021): 337. http://dx.doi.org/10.3390/jrfm14070337.
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One of the notable features of bitcoin is its extreme volatility. The modeling and forecasting of bitcoin volatility are crucial for bitcoin investors’ decision-making analysis and risk management. However, most previous studies of bitcoin volatility were founded on econometric models. Research on bitcoin volatility forecasting using machine learning algorithms is still sparse. In this study, both conventional econometric models and a machine learning model are used to forecast the bitcoin’s return volatility and Value at Risk. The objective of this study is to compare their out-of-sample performance in forecasting accuracy and risk management efficiency. The results demonstrate that the RNN outperforms GARCH and EWMA in average forecasting performance. However, it is less efficient in capturing the bitcoin market’s extreme events. Moreover, the RNN shows poor performance in Value at Risk forecasting, indicating that it could not work well as the econometric models in explaining extreme volatility. This study proposes an alternative method of bitcoin volatility analysis and provides more motivation for economic researchers to apply machine learning methods to the less volatile financial market conditions. Meanwhile, it also shows that the machine learning approaches are not always more advanced than econometric models, contrary to common belief.
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Mazreku, Ibish, Fisnik Morina, and Florentina Zeqaj. "Does working capital management affect the profitability of commercial banks: the case of Kosovo." European Journal of Sustainable Development 9, no. 1 (February 1, 2020): 126. http://dx.doi.org/10.14207/ejsd.2020.v9n1p126.
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Purpose: This paper aims to analyze working capital and its impact on the profitability of commercial banks. The other objectives of this study are to analyze the factors that influence the profitability of commercial banks, to find out the relationship between profitability and working capital management. To achieve these research objectives, several research questions have been posited: How much does working capital affect the profitability of commercial banks? What are the relationships between bank profitability and bank size, debt ratio and current ratio? What are the other factors affecting the profitability of commercial banks?
Methodology: The empirical data to be used in this research are secondary data and will be based on annual reports of commercial banks and reports of the Central Bank of Kosovo. From these data, some indicators such as return on assets, current ratio, debt ratio and banks’ size will be calculated. This research covers a period of 5 years and the data will be analyzed and interpreted through econometric models. In addition, to analyze the impact of working capital on the profitability of commercial banks in Kosovo, trend analysis will also be applied through the comparative method.
Findings: Based on the empirical results, we can conclude that bank size and the current ratio have positively affected the performance of commercial banks in Kosovo, whereas the debt ratio has had a negative effect. All the independent variables in relation to the dependent variable (ROA) are at the standard level of significance P-value = 0.05.
Practical implications: Through this study we can recommend all commercial banks in Kosovo to invest much more in working capital, since financial investments in working capital affect the bank's profitability. This means that a high investment in the elements of working capital can lead to increased bank profitability, whereas its profitability decreases when investment in working capital is low.
Originality: This paper presents real and sustainable results with respect to the conclusions. The period analyzed (2013-2017) is a persuasive period for drawing competent conclusions and recommendations.
Keywords: working capital, debt ratio, current ratio, bank size, return on assets
JEL Classification: G2, G20, G21, G3, G32, D24
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Sievka, Victoria, Igor Shevchuk, Aleksey Stepanov, and Oksana Tykhankina. "Application of cluster models in forecasting housing construction economic potential in the region." E3S Web of Conferences 217 (2020): 11006. http://dx.doi.org/10.1051/e3sconf/202021711006.
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The article introduces the first econometric modeling of the needs in new housing construction, reconstruction, capital repairs and finishing of uncompleted construction objects in the region on the basis of cluster models. Forecasting diagrams of gaps between the existing economic potential of housing construction and a normative need in sector housing as well as the need in introducing sector housing to reach mean European standards of housing are plotted.
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Wilson, Christine A. "Feeder Cattle Forecasting Models: An Econometric Study of Development and Performance." American Journal of Agricultural Economics 75, no. 5 (December 1993): 1326–32. http://dx.doi.org/10.2307/1243478.
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Sun, Wenxiang, Jisheng Peng, Juelin Ma, and Weiguo Zhong. "Evolution and performance of Chinese technology policy." Journal of Technology Management in China 4, no. 3 (September 25, 2009): 195–216. http://dx.doi.org/10.1108/17468770911013528.
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PurposeThe purpose of this paper is to analyze the evolution of Chinese technology policy, assess its technological and economic performance from the visual angle of “market in exchange for technology” strategy.Design/methodology/approachA quantified method based on policy contents from policy power, policy goals and policy means was developed to build a policy database, and analyze the evolutionary tendency of Chinese technology policy. In addition, econometric models were built to assess the performance of technology policy.FindingsThe critical goals of Chinese technology policy are introducing technology directly or indirectly by introducing foreign investment and innovation, but the critical linkage between introduction and innovation‐technology absorption was absent – almost all policy means aim at the introduction of foreign investment and innovation but not technology absorption. More unfortunately, the econometric results show that introduction of foreign investment contributes little, while technology absorption contributes much more. Institutional path‐dependence and the competition for benefits among different departments have aggravated an already unbalanced emphasis on technology policies during the reform.Research limitations/implicationsDuring the quantification of technology policy, one perhaps loses some information about policy, and it can only be used to analyze the technology policy system, not special technology policy.Practical implicationsAnalyses of the evolution of Chinese technology policy and econometric results show the blunder of “market in exchange for technology” strategy from policy formulation and execution. Also, it leads to the optimization of technology policy from policy targets, implements based on national technology and innovation strategy.Originality/valueThe paper develops the method of technology policy quantification and builds econometric models to assess the contribution of technology policy to technology progress and economy development.
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Zhu, Xian Cheng, Zhi Peng Zhang, and Kun Qian. "The Econometric Model of Resource Efficiency Based on Emergy Theory." Advanced Materials Research 403-408 (November 2011): 1552–54. http://dx.doi.org/10.4028/www.scientific.net/amr.403-408.1552.
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The paper defined the connotation of resource efficiency, and utilized the emergy theory and language to convert different resources which occured input, output and negative effects in the of regional economic system into the amount of the energy value of unified standards, and also established the econometric model of resource efficiency. The author scientifically explained and empirically analyzed the model utilizing emergy symbols, which provided a new theoretical models and methods for measuring resource efficiency.
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Karmeliuk, Hanna, Svitlana Plaskon, and Halyna Seniv. "Econometric estimation of the pension in Ukraine." Herald of Ternopil National Economic University, no. 2(84) (May 31, 2017): 48–59. http://dx.doi.org/10.35774//visnyk2017.02.048.
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The research paper analyzes the dynamics of minimum and average pensions, minimum wage, living wage, consumer price index, and gross external debt of Ukraine. The causal connections between the minimum pension and the researched parameters are presented in UAH and dollar terms. The necessity of econometric modeling for studying socio-economic indicators of living standards is highlighted. The main trends of the impact of the minimum wage, the living wage, the consumer price index, the gross external debt on the minimum pension are overviewed. The predicted values of the minimum pension in Ukraine in UAH in 2017-2021 are calculated, and the confidence intervals of them with a high degree of confidence are given. The ratio of the minimum pension to the minimum wage in UAH and dollar terms is calculated. The econometric models of the dependencies of minimum pension on the minimum wage are presented in UAH and dollar terms. According to econometric models a rise of the minimum wage is accompanied by a rise of the minimum pension. The econometric models of the dependencies of the minimum pension on the subsistence minimum in UAH and dollar terms are presented. According to the models, a rise of the subsistence minimum is accompanied by an increase in the minimum pension. Also, the econometric models of the dependencies of the minimum pension on the consumer price index in UAH and dollar terms are developed. The econometric models prove that a rise of the inflation rate leads to a rise of the minimum pension. Since 2014 the growth of consumer price index has been accompanied by a rapid decline of the minimum pension in dollar terms. The econometric model which shows the dependence of the consumer price index on the minimum pension is developed in UAH and dollar terms. From the model it follows that an increase of the minimum pension results in higher inflation. The econometric models of the dependencies of the minimum pension on the gross external debt are presented in UAH and dollar terms. It is shown that by 2014, foreign loans in UAH and dollar terms were welcome in order to raise pensions which led to the rapid rise of the latter. In recent years the growth of debt in the UAH slightly affected the growth of the minimum pension in UAH, whereas the growth of debt in dollars led to a significant decline in the minimum pension in dollar terms.
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Lahouel, Noureddine, and Slaheddine Hellara. "Improving the option pricing performance of GARCH models in inefficient market." Investment Management and Financial Innovations 17, no. 2 (April 23, 2020): 14–25. http://dx.doi.org/10.21511/imfi.17(2).2020.02.
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Understanding the relation between option pricing and market efficiency is important. Indeed, emphasizing this relation generates new insights that are appropriate in practice. These insights give a better understanding of the current limitations of the option pricing and hedging methods. This article thus aims to improve the performance of the option pricing approach. To start, the relation between the option pricing methodology and the informational market efficiency was discussed. It is, therefore, useful, before proceeding to apply the standard risk-neutral approach, to check the efficiency assumption. New modified GARCH processes were used to model the dynamics of the asset returns in the option pricing framework. The new considered approaches allow describing the dynamic of returns when the market is inefficient. Using real data on CAC 40 index, the performance of different models as a function of maturity and moneyness was studied. The in-sample analysis, interested in the stability of the pricing models across time, showed that the new approach, developed under the affine GARCH process, is the most accurate. The study of the out-of-sample performance, which aims to evaluate the forecasting ability of different approaches, confirmed the results of the in-sample analysis. For the optional portfolio hedging, always the best hedging approach is that obtained under the affine GARCH model. After a regression study, it was found that the difference between theoretical and observed option values can be explained by factors, which are not taken into account in the proposed pricing formulae.
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RATNER, Svetlana V., and Valerii V. IOSIFOV. "Tools for practical implementation of climate policy in transport: Econometric analysis of global experience." National Interests: Priorities and Security 17, no. 12 (December 14, 2021): 2272–94. http://dx.doi.org/10.24891/ni.17.12.2272.
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Subject. The article addresses the standards for greenhouse gas emissions that are currently considered as an effective tool for stimulating the development of alternative transport technologies. However, quantitative evaluation of their effectiveness is not available, which is partially explained by the lack of statistical information from different countries. Objectives. The purpose is to build econometric models of the influence of these standards on the electric car market development. Methods. The annual reports of the International Energy Agency on the development of the electric car market and the data of the Global EV Data Explorer statistics center serve as the information base of the study. We analyzed time series for indicators of sales of electric cars in different countries and built mixed models, considering the auto-regression component, which helps describe the internal dynamics of the electric car market. Results. The obtained regression coefficients in models for various countries can be used as interval evaluations for forecasting the growth of electric car sales in Russia, given the necessary conditions for developing a charging infrastructure and creating a system of incentives to match the cost of electric cars to that of traditional vehicles. Conclusions. These interval evaluations may be useful for further decisions on the development of charging infrastructure, planning for resource use for electricity generation, calculating optimal subsidy or tax relief to support electric cars, evaluating the economic consequences of introducing the new standards on CO2 emissions, etc.
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Jiao, Eden Xiaoying, and Jason Li Chen. "Tourism forecasting: A review of methodological developments over the last decade." Tourism Economics 25, no. 3 (November 26, 2018): 469–92. http://dx.doi.org/10.1177/1354816618812588.
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This study reviewed 72 studies in tourism demand forecasting during the period from 2008 to 2017. Forecasting models are reviewed in three categories: econometric, time series and artificial intelligence (AI) models. Econometric and time series models that have already been widely used before 2007 remained their popularity and were more often used as benchmark models for forecasting performance evaluation and comparison with respect to new models. AI models are rapidly developed in the past decade and hybrid AI models are becoming a new trend. And some new trends with regard to the three categories of models have been identified, including mixed frequency, spatial regression and combination and hybrid models. Different combination components and combination techniques have been discussed. Results in different studies proved superiority of combination forecasts over average single forecasts performance.
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Tetteh, Iuliia, Michael Boehlje, Anil K. Giri, and Sankalp Sharma. "Strategic behavior of nontraditional lenders in agricultural credit markets." Agricultural Finance Review 82, no. 2 (December 2, 2021): 379–96. http://dx.doi.org/10.1108/afr-06-2021-0074.
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PurposeThis paper examines credit products, operational performance and business models employed by nontraditional lenders (NTLs) in agricultural credit markets.Design/methodology/approachTwo research methods were employed in this study: (1) an executive interview to collect primary data and (2) a case study approach to analyze the findings and develop insights.FindingsThe findings indicate the presence of significant differences among lenders across and within three categories of NTLs (large volume, vendor financing and collateral-based NTLs). For example, collateral-based NTLs employ different strategies focusing on types of loans, funding sources, commodities they support and geographic coverage to further segment the market. NTLs in this study were able to capture market by successfully identifying gaps in the supply side of agricultural credit and developing products that meet the needs of that niche (e.g. heavy renters, large operations, producers seeking fixed interest rates for term loans, financially fragile producers). Most of the interviewed NTLs had credit standards comparable to those of traditional lenders and consider them both competitors and partners since many NTLs partner with traditional lenders on participation loans, loan servicing and/or sourcing funds.Originality/valueThe supply side of a nontraditional lending has not been studied extensively due to the proprietary nature of data. The executive interviews conducted in this study allowed for accumulation of industry data, which is not available otherwise.
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Duguleana, Constantin, Liliana Duguleana, Camelia Mirela Baba, and Cristina Drumea. "Recovery after Demerger: Evidence from Romanian Companies." Sustainability 14, no. 3 (January 20, 2022): 1151. http://dx.doi.org/10.3390/su14031151.
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The paper follows the demerger phenomenon in Romania in order to find out whether companies regain their economic performance after reorganization. The research is based on four samples of companies, divided into 2012, 2013, 2014, and 2015, that recorded their financial indicators in the period from 2005–2019. Using the financial indicators of companies that demerged in the same year, we analyzed the economic performances before and after the demergers, using statistical and econometric methods. The model with the fixed effects of the cross sections proved to be the most suitable for each panel, both for the entire analyzed period and for the two subperiods: ante and post demerger. The subperiod models are better than the panel econometric models for the entire period. The results show that all of the Romanian companies recovered after the demergers, and also to what extents. The validities of the econometric models confirm the sustainability of the economic activities after the demergers. This paper provides a study methodology and econometric models to investigate the demerger phenomenon among Romanian companies.
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Simionescu, Bratu Mihaela. "Predicting Macroeconomic Indicators in the Czech Republic Using Econometric Models and Exponential Smoothing Techniques." South East European Journal of Economics and Business 7, no. 2 (November 1, 2012): 89–99. http://dx.doi.org/10.2478/v10033-012-0017-3.
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Abstract Econometric modeling and exponential smoothing techniques are two quantitative forecasting methods with good results in practice, but the objective of the research was to find out which of the two techniques are better for short run predictions. Therefore, for inflation, unemployment and interest rate in the Czech Republic various accuracy indicators were calculated for the predictions based on these methods. Short run forecasts on a horizon of 3 months were made for December 2011-February 2012, the econometric models being updated. For the Czech Republic, the exponential smoothing techniques provided more accurate forecasts than the econometric models (VAR(2) models, ARMA procedure and models with lagged variables). One explication for the better performance of smoothing techniques would be that in the chosen countries the short run predictions were more influenced by the recent evolution of the indicators.
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Arize, Augustine C., Ioannis N. Kallianiotis, Ebere Eme Kalu, John Malindretos, and Moschos Scoullis. "A Multidude of Econometric Tests: Forecasting the Dutsch Guilder." International Journal of Economics and Finance 9, no. 9 (August 10, 2017): 94. http://dx.doi.org/10.5539/ijef.v9n9p94.
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This paper studies a diversity of exchange rate models, applies both parametric and nonparametric techniques to them, and examines said models’ collective predictive performance. We shall choose the forecasting predictor with the smallest root mean square forecast error (RMSE); the empirical evidence for a better type of exchange rate model is in equation (34), although none of our evidence gives an optimal forecast. At the end, these models’ error correction versions will be fit so that plausible long-run elasticities can be imposed on each model’s fundamental variables.
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Rodríguez-Póo, Juan M., Stefan Sperlich, and Philippe Vieu. "SPECIFICATION TESTING WHEN THE NULL IS NONPARAMETRIC OR SEMIPARAMETRIC." Econometric Theory 31, no. 6 (September 18, 2014): 1281–309. http://dx.doi.org/10.1017/s0266466614000504.
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This paper discusses the problem of testing misspecifications in semiparametric regression models for a large family of econometric models under rather general conditions. We focus on two main issues that typically arise in econometrics. First, many econometric models are estimated through maximum likelihood or pseudo-ML methods like, for example, limited dependent variable or gravity models. Second, often one might not want to fully specify the null hypothesis. Instead, one would rather impose some structure like separability or monotonicity. In order to address these points we introduce an adaptive omnibus test. Special emphasis is given to practical issues like adaptive bandwidth choice, general but simple requirements on the estimates, and finite sample performance, including the resampling approximations.
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Lazarides, Themistokles, Evaggelos Drimpetas, and George Kyriazopoulosr. "Mergers, liquidations and bankruptcies in the European banking sector." Risk Governance and Control: Financial Markets and Institutions 5, no. 2 (2015): 52–70. http://dx.doi.org/10.22495/rgcv5i2art6.
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The inactivity of banks may be the result of a number of events, such as merger & acquisition (M&A), liquidation, default-bankruptcy, etc. All these phenomena of inactivity contribute to the same result, the reform of the European banking sector and they may have the same causes. The paper will address the issue of inactivity and will try to detect its causes using econometric models. Six groups of indicators are examined: performance, size, ownership, corporate governance, capital adequacy or capital structure and loan growth. Three econometric methods (Probit, Logit, OLS) have been used to create a system that predicts inactivity. The results of the econometric models show that from the six groups of indicators, four have been found to be statistically important (performance, size, ownership, corporate governance). Two have a negative impact (ownership, corporate governance) on the probability of inactivity and two positive (performance, size). The paper’s value and innovation is that it has given a systemic approach to find indicators of inactivity and it has excluded two groups of indicators as non-statistically important (capital adequacy or capital structure and growth).
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Tsvil, Mariya, and O. Abramova. "ECONOMETRIC MODELING OF INDIVIDUAL ECONOMIC INDICATORS OF THE ACTIVITY OF CUSTOMS AUTHORITIES." Science & World 2022, no. 4 (December 16, 2022): 26–30. http://dx.doi.org/10.26526/2307-9401-2022-4-26-30.
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The article represents the theoretical, regulatory consolidated information on the effectiveness indicesof the performance of the customs authorities, as well as an econometric modeling of the separate parameters of such economic indicators as customs payments, namely weight and cost. The developed models according to the given parameters are based on the monthly data of the Customs statistics for commodity group 23 «Residues and wastes of the food industry; prepared animal feed» for 2018-2021. By means of the constructed econometric models, the values of the customs value and weight for this category of goods for January 2022 have been predicted.
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Dixon, Tim. "Commercial property retrofitting." Journal of Property Investment & Finance 32, no. 4 (July 1, 2014): 443–52. http://dx.doi.org/10.1108/jpif-02-2014-0016.
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Purpose – Progress in retrofitting the UK's commercial properties continues to be slow and fragmented. New research from the UK and USA suggests that radical changes are needed to drive large-scale retrofitting, and that new and innovative models of financing can create new opportunities. The purpose of this paper is to offer insights into the terminology of retrofit and the changes in UK policy and practice that are needed to scale up activity in the sector. Design/methodology/approach – The paper reviews and synthesises key published research into commercial property retrofitting in the UK and USA and also draws on policy and practice from the EU and Australia. Findings – The paper provides a definition of “retrofit”, and compares and contrasts this with “refurbishment” and “renovation” in an international context. The paper summarises key findings from recent research and suggests that there are a number of policy and practice measures which need to be implemented in the UK for commercial retrofitting to succeed at scale. These include improved funding vehicles for retrofit; better transparency in actual energy performance; and consistency in measurement, verification and assessment standards. Practical implications – Policy and practice in the UK needs to change if large-scale commercial property retrofit is to be rolled out successfully. This requires mandatory legislation underpinned by incentives and penalties for non-compliance. Originality/value – This paper synthesises recent research to provide a set of policy and practice recommendations which draw on international experience, and can assist on implementation in the UK.