TY - JOUR AU - Núñez, Héctor M AU - Otero, Jesús TI - A one covariate at a time, multiple testing approach to variable selection in high‐dimensional linear regression models: A replication in a narrow sense T2 - Journal of Applied Econometrics VL - 36 IS - 6 SP - 833-841 PY - 2021 DA - 2021 AB - Summary: Chudik, Kapetanios, & Pesaran (Econometrica 2018, 86, 1479‐1512) propose a one covariate at a time, multiple testing (OCMT) approach to variable selection in high‐dimensional linear regression models as an alternative approach to penalised regression. We offer a narrow replication of their key OCMT results based on the Stata software instead of the original MATLAB routines. Using the new user‐written Stata commands baing and ocmt, we find results that match closely those reported by these authors in their Monte Carlo simulations. In addition, we replicate exactly their findings in the empirical illustration, which relate to top five variables with highest inclusion frequencies based on the OCMT selection method. [ABSTRACT FROM AUTHOR] SN - 0883-7252 UR - https://search-ebscohost-com.ez.urosario.edu.co/login.aspx?direct=true&AuthType=ip&db=bth&AN=153092490&lang=es&site=eds-live&scope=site KW - Monte Carlo method, Regression analysis, high‐dimensional models, linear regression, OCMT, variable selection ER - TY - JOUR AU - Chudik, Alexander AU - Kapetanios, George AU - Pesaran, Hashem TI - A One Covariate at a Time, Multiple Testing Approach to Variable Selection in High-Dimensional Linear Regression Models T2 - Chudik , A , Kapetanios , G & Pesaran , H 2018 , ' A One Covariate at a Time, Multiple Testing Approach to Variable Selection in High-Dimensional Linear Regression Models ' ECONOMETRICA PY - 2018 DA - 2018 AB - This paper provides an alternative approach to penalised regression for model selection in the context of high dimensional linear regressions where the number of covariates is large, often much larger than the number of available observations. We consider the statistical significance of individual covariates one at a time, whilst taking full account of the multiple testing nature of the inferential problem involved. We refer to the proposed method as One Covariate at a Time Multiple Testing (OCMT) procedure, and use ideas from the multiple testing literature to control the probability of selecting the approximating model, the false positive rate and the false discovery rate. OCMT is easy to interpret, relates to classical statistical analysis, is valid under general assumptions, is faster, and performs well in small samples. The usefulness of OCMT is also illustrated by an empirical application to forecasting U.S. output growth and inflation. UR - https://search-ebscohost-com.ez.urosario.edu.co/login.aspx?direct=true&AuthType=ip&db=edsbas&AN=edsbas.95E729BD&lang=es&site=eds-live&scope=site ER - TY - JOUR AU - Castro, Carlos TI - Sistema de modelos multivariados para la proyección del Producto Interno Bruto T2 - Archivos de Economía PY - 2003 DA - 2003 AB - En el presente artículo se desarrolla un sistema de modelos multivariados para la construcción de pronósticos del PIB colombiano. El sistema desarrollado incorpora los criterios de decisión (automatizados) tradicionales de la literatura de modelos multivariados para el proceso de identificación y de evaluación de pronósticos mediante criterios ex-post y ex-ante. Utilizando este sistema se realizaron diferentes ejercicios para identificar un conjunto de variables que de acuerdo a la evolución histórica (1992-2002) de la serie del producto permitan construir un modelo econométrico multivariado que genere los mejores pronósticos de la evolución reciente del producto. Los resultados de los ejercicios resaltan la importancia del modelo de referencia (univariado) en la construcción de pronósticos, ilustran la dificultad de establecer reglas de pronóstico y permiten identificar las variables denominadas de actividad económica y las variables monetarias y financieras como las UR - https://search-ebscohost-com.ez.urosario.edu.co/login.aspx?direct=true&AuthType=ip&db=edsrep&AN=edsrep.p.col.000118.003502&lang=es&site=eds-live&scope=site KW - PIB ER - TY - JOUR AU - Carlos, Capistrán AU - Gabriel, López-Moctezuma TI - LAS EXPECTATIVAS MACROECONÓMICAS DE LOS ESPECIALISTAS: Una evalución de pronósticos de corto plazo en México T2 - El Trimestre Económico VL - 77 IS - 306(2) SP - 275-312 PY - 2010 DA - 2010 AB - Se analiza los pronósticos de inflación, tipo de cambio, tasa de interés y crecimiento del PIB para horizontes de corto plazo contenidos en la Encuesta sobre Expectativas de los Especialistas en Economía del Sector Privado que recaba mensualmente el Banco de México. El estudio se enfoca en el pronóstico de consenso para el periodo de enero de 1995 a abril de 2008. Se examina la eficiencia en el uso de información, así como el desempeño relativo de los pronósticos de la encuesta utilizando como referencia pronósticos sencillos de series de tiempo, macroeconómicos y financieros. Se encuentra que los pronósticos de consenso de los especialistas, en general, no superan pruebas de ausencia de sesgo, de ausencia de autocorrelación en exceso o de uso de información pública, lo que sugiere oportunidades para mejorar dichos pronósticos. Sin embargo, los pronósticos de consenso parecen ser, en general, más precisos que los pronósticos de referencia, aunque al analizar una muestra que empieza en SN - 0041-3011 UR - https://search-ebscohost-com.ez.urosario.edu.co/login.aspx?direct=true&AuthType=ip&db=edsjsr&AN=edsjsr.20857255&lang=es&site=eds-live&scope=site ER - TY - JOUR AU - Lu, Shaobo TI - Research on GDP Forecast Analysis Combining BP Neural Network and ARIMA Model T2 - Computational Intelligence & Neuroscience SP - 1-10 PY - 2021 DA - 2021 AB - Based on the BP neural network and the ARIMA model, this paper predicts the nonlinear residual of GDP and adds the predicted values of the two models to obtain the final predicted value of the model. First, the focus is on the ARMA model in the univariate time series. However, in real life, forecasts are often affected by many factors, so the following introduces the ARIMAX model in the multivariate time series. In the prediction process, the network structure and various parameters of the neural network are not given in a systematic way, so the operation of the neural network is affected by many factors. Each forecasting method has its scope of application and also has its own weaknesses caused by the characteristics of its own model. Secondly, this paper proposes an effective combination method according to the GDP characteristics and builds an improved algorithm BP neural network price prediction model, the research on the combination of GDP prediction model is currently mostly foc SN - 1687-5265 UR - https://search-ebscohost-com.ez.urosario.edu.co/login.aspx?direct=true&AuthType=ip&db=a9h&AN=153550963&lang=es&site=eds-live&scope=site KW - ARTIFICIAL neural networks, FORECASTING, GROSS domestic product, PREDICTION models, BOX-Jenkins forecasting, ALGORITHMS, ECONOMIC forecasting ER - TY - JOUR AU - Ana Arencibia, Pareja AU - Ana, Gomez-Loscos AU - Mercedes de Luis, López AU - Gabriel, Perez-Quiros TI - A Short Term Forecasting Model for the Spanish GDP and its Demand Components T2 - Economía, Vol 43, Iss 85 (2020 PY - 2020 DA - 2020 AB - This paper proposes a new version of the Spain-STING (Spain, Short-Term INdicator of Growth), a dynamic factor model used by the Banco de España for the short-term forecasting of the Spanish economy. The extended and revised version of the Spain-STING presented in this document includes a forecast for each of the demand components of the National Accounts. In order to select the indicators that best estimate the Spanish GDP and its demand components, several models are considered. Following this strategy, the selected models are those in which the common factor explains the highest proportion of the variance of the GDP. These models allow us to forecast GDP, private consumption, public expenditure, investment in capital goods, construction investment, exports and imports in a consistent way. We assess the predictive power of the models for GDP and its demand components for the period 2005–2017. With regard to the GDP forecast, we find some improvement of the predictive power compared SN - 0254-4415 UR - https://search-ebscohost-com.ez.urosario.edu.co/login.aspx?direct=true&AuthType=ip&db=edsbas&AN=edsbas.32607891&lang=es&site=eds-live&scope=site KW - Business cycles, Spanish economy, Dynamic Factor models, Economic growth, development, planning, HD72-88, Economic history and conditions, HC10-1085, Economics as a science, HB71-74 ER - TY - JOUR AU - Wiberg Daniel Assistant, Professor AU - Högberg Andreas Ph.D., Candidate AU - Lidbom Marie Research, Assistant AU - Internationella Handelshögskolan Högskolan i Jönköping Internationella Handelshögskolan IHH, Nationalekonomi TI - Forecasting GDP Growth The Case of The Baltic States PY - 2009 DA - 2009 AB - The purpose of this thesis is to identify a general model to forecast GDP growth for the Baltic States, Estonia, Latvia and Lithuania. If the model provides reliable results for these states, then the model should be able to forecast GDP growth for other countries of interest. Forecasts are made by using a reduced vector autoregressive (VAR) model. The VAR models make use of past values of Gross Domestic Product-Inflation-Unemployment as explanatory variables.The performed forecasts have provided good results for horizons up to t+8. The forecasts for 2009 (t+12) are in line with those of several other actors. It is reasonable to assume that some of the forecasts for t+16 have reliable results. The Lithuanian forecast show a fall in GDP with 12.51 per cent in 2009 and a GDP growth of 4.23 per cent in 2010. The forecast for Estonia show that the GDP will decrease with 1.49 per cent in 2009 and 12.72 per cent in 2010. Finally the forecast for Latvia show a fall in GDP of 3.1 pe UR - https://search-ebscohost-com.ez.urosario.edu.co/login.aspx?direct=true&AuthType=ip&db=edseur&AN=edseur.https%3a..www.europeana.eu.item.9200111.BibliographicResource.1000085966832%3futm.source%3dapi%26utm.medium%3dapi%26utm.campaign%3dYuvuWBeCa&lang=es&site=eds-live&scope=site KW - Student thesis, book ER - TY - JOUR AU - Toacă, Zinovia AU - Vîntu, Denis TI - Model trimestrial de Prognoză a PIB-ului Republicii Moldova[Quarterly GDP Forecast Model of the Republic of Moldova] T2 - MPRA Paper PY - 2019 DA - 2019 AB - The purpose of the present paper is to describe a model of quarterly GDP forecast, categories of uses, in accordance with the development priorities of the Republic of Moldova in the medium term. The achievement of the main purpose requires to draw up the tasks, among which: - Conceptual approach of time series, with reference to the use of ARIMA technique for estimating the time series; - Economic analysis of the categories of uses, subcomponents of GDP; - Studying time series, using method of indices, where the following indicators were used as: growth rate, structure, degree of influence and influence; - Forecast of categories of uses, for the same reference period 2019-2020 Actuality of the research - Use of the ARIMA technique; - Using econometric package Eviews for estimating and developing the macroeconometric model. Scientific and methodological approaches described in this paper will serve as scientific support for the Ministry of Economy in the process of developing their ow UR - https://search-ebscohost-com.ez.urosario.edu.co/login.aspx?direct=true&AuthType=ip&db=edsrep&AN=edsrep.p.pra.mprapa.107565&lang=es&site=eds-live&scope=site KW - Forecast, ARIMA, general domestic product, Student test, Jarque-Bera, Fischer. ER - TY - JOUR AU - Li, Ge AU - Bo, Cui TI - Research on forecast of GDP based on process neural network T2 - 2011 Seventh International Conference on Natural Computation, Natural Computation (ICNC), 2011 Seventh International Conference on VL - 2 SP - 821-824 PY - 2011 DA - 2011 AB - For the multivariate forecast of Gross Domestic Product (GDP), the common features of traditional forecast methods are difficult to express the time cumulative effects in real forecast, and on the other hand, the factors influencing GDP have very typical timing characteristics. Therefore, in consideration of increasing GDP forecast accuracy, process neural network (PNN) was used into the GDP forecast. Making use of the feature of time-varying input function in PNN, the time and space cumulative effect of GDP influence factors was adequately considered into the forecast, and penalty factor was introduced to PNN training to improve BP algorithm. The GDP forecast model of Heilongjiang Province was established based on the above improved algorithm and it was compared and analyzed with the traditional method. The result shows that the PNN model has higher accuracy. UR - https://search-ebscohost-com.ez.urosario.edu.co/login.aspx?direct=true&AuthType=ip&db=edseee&AN=edseee.6022203&lang=es&site=eds-live&scope=site KW - Economic indicators, Neurons, Biological neural networks, Predictive models, Training, Analytical models, penalty factor, artificial neural network, process neural network, GDP forecast ER - TY - JOUR AU - Espinoza, Raphael AU - Fornari, Fabio AU - Lombardi, Marco J TI - The Role of Financial Variables in predicting economic activity T2 - Journal of Forecasting VL - 31 IS - 1 SP - 15-46 PY - 2012 DA - 2012 AB - ABSTRACT Previous research found that the US business cycle leads the European one by a few quarters, and can therefore be useful in predicting euro area gross domestic product (GDP). In this paper we investigate whether additional predictive power can be gained by adding selected financial variables belonging to either the USA or the euro area. We use vector autoregressions (VARs) that include the US and euro area GDPs as well as growth in the Rest of the World and selected combinations of financial variables. Out-of-sample root mean square forecast errors (RMSEs) evidence that adding financial variables produces a slightly smaller error in forecasting US economic activity. This weak macro-financial linkage is even weaker in the euro area, where financial indicators do not improve short- and medium-term GDP forecasts even when their timely availability relative to GDP is exploited. It can be conjectured that neither US nor European financial variables help predict euro area GDP as th SN - 0277-6693 UR - https://search-ebscohost-com.ez.urosario.edu.co/login.aspx?direct=true&AuthType=ip&db=bth&AN=69971810&lang=es&site=eds-live&scope=site KW - Economic activity, Business cycles, Financial economics, Gross domestic product, Standard deviations, Economic statistics, Vector autoregression model, Mathematical variables, conditional forecast, financial variables, international linkages, VAR ER - TY - JOUR AU - Divya, K Hema AU - Devi, V Rama TI - A Study on Predictors of GDP: Early Signals T2 - Procedia Economics and Finance VL - 11 SP - 375-382 PY - 2014 DA - 2014 AB - Financial Architecture aims sustainability of an economy by ensuring consistent growth rate.GDP is an indicator of the growth of an economy. Higher GDP of an economy reflects robust growth of an economy and vice-versa and as such every country tries to maximise the growth rate of GDP .There are certain macro factors operating in the economic environment that will influence the GDP growth rate. The study makes an attempt to determine the influence of selected economic variables namely Inflation, Exchange rate, Foreign exchange reserves, FII's, Sensex, Balance of Payments and Current Fiscal Deficit on the GDP of an economy. The data is collected by using secondary sources relating to the selected Economic variables. The data is collected for a period of 15 years i.e. from 01-04-1997 to 31-03-2012 with annual intervals. The scope of the study is confined only to selected economic variables only. Correlation and ANOVA are used for analyzing the relationship between the GDP and selected ec SN - 2212-5671 UR - https://search-ebscohost-com.ez.urosario.edu.co/login.aspx?direct=true&AuthType=ip&db=edselp&AN=S2212567114002056&lang=es&site=eds-live&scope=site KW - GDP, Economic variables, Financial Architecture ER - TY - JOUR AU - Duo, Qin AU - Marie Anne, Cagas AU - Geoffrey, Ducanes AU - Nedelyn, Magtibay-Ramos AU - Pilipinas, Quising TI - Forecasting Inflation and GDP Growth: Automatic Leading Indicator (ALI) Method versus Macro Econometric Structural Models (MESMS) ; ERD Technical Notes ; 18 PY - 2006 DA - 2006 AB - This paper compares the forecast performance of the automatic leading indicator (ALI) method with the macro econometric structural model (MESM) and seeks ways of improving the ALI method. Inflation and gross domestic product growth form the forecast objects for comparison, using data from People’s Republic of China, Indonesia, and Philippines. The ALI method is found to produce better forecasts than MESMs in general, but the method is found to involve greater uncertainty in choosing indicators, mixing data frequencies, and utilizing unrestricted vector auto-regressions. Two possible improvements are found helpful to reduce the uncertainty: (i) give theory priority in choosing indicators and include theory-based disequilibrium shocks in the indicator sets; and (ii) reduce the vector auto-regressions by means of the general → specific model reduction procedure. SN - 1655-5236 UR - https://search-ebscohost-com.ez.urosario.edu.co/login.aspx?direct=true&AuthType=ip&db=edsbas&AN=edsbas.B8D11A36&lang=es&site=eds-live&scope=site KW - Free Trade, Trade, Trade Agreements, Regional Economic Integration, Exports, Economic integration, Distribution, Development Bank, Trade policy, Euro, Inflation, Business, Finance ER - TY - JOUR AU - Alcides de Jesús Padilla, Sierra TI - Uso de variables de actividad económica en la estimación del PIB per cápita microterritorial T2 - Cuadernos de Economía VL - 34 IS - 65 SP - 349-376 PY - 2015 DA - 2015 AB - En este estudio se propone una metodología para calcular el producto interno bruto (PIB) per cápita de las principales ciudades de Colombia. Para este objetivo se utilizan algunas variables proxy de la actividad económica. Como resultado se señala que, a diferencia de estudios previos, el consumo de energía y el número de líneas telefónicas resultaron determinantes de la actividad económica urbana. SN - 0121-4772 UR - https://search-ebscohost-com.ez.urosario.edu.co/login.aspx?direct=true&AuthType=ip&db=edsdoj&AN=edsdoj.85cdac5d21dd43f58656332c36b36109&lang=es&site=eds-live&scope=site KW - medición del PIB per cápita, modelación econométrica, economía regional, Social Sciences, Economic history and conditions, HC10-1085 ER - TY - JOUR AU - Stock, James H AU - Watson, Mark W TI - Macroeconomic Forecasting Using Diffusion Indexes T2 - Journal of Business and Economic Statistics VL - 20 IS - 2 SP - 147-162 PY - 2002 DA - 2002 SN - 0735-0015 UR - https://search-ebscohost-com.ez.urosario.edu.co/login.aspx?direct=true&AuthType=ip&db=eoh&AN=0608937&lang=es&site=eds-live&scope=site KW - Forecasting Models KW - Simulation Methods C53, General Aggregative Models: Forecasting and Simulation: Models and Applications E17 ER - TY - JOUR AU - Bai, Jushan AU - Ng, Serena TI - Determining the Number of Factors in Approximate Factor Models T2 - Econometrica VL - 70 IS - 1 SP - 191-221 PY - 2002 DA - 2002 AB - In this paper we develop some econometric theory for factor models of large dimensions. The focus is the determination of the number of factors (r), which is an unresolved issue in the rapidly growing literature on multifactor models. We first establish the convergence rate for the factor estimates that will allow for consistent estimation of r. We then propose some panel criteria and show that the number of factors can be consistently estimated using the criteria. The theory is developed under the framework of large cross-sections (N) and large time dimensions (T). No restriction is imposed on the relation between N and T. Simulations show that the proposed criteria have good finite sample properties in many configurations of the panel data encountered in practice. SN - 0012-9682 UR - https://search-ebscohost-com.ez.urosario.edu.co/login.aspx?direct=true&AuthType=ip&db=edsjsr&AN=edsjsr.2692167&lang=es&site=eds-live&scope=site KW - Factor Analysis, Asset Pricing, Principal Components, Model Selection, Factor analysis, Estimation methods, Econometric factor models, Eigenvalues, Macroeconomics, Economic models, Arbitrage, Modeling, Infinity, Covariance matrices ER - TY - JOUR AU - Onatski, Alexei TI - DETERMINING THE NUMBER OF FACTORS FROM EMPIRICAL DISTRIBUTION OF EIGENVALUES T2 - The Review of Economics and Statistics VL - 92 IS - 4 SP - 1004-1016 PY - 2010 DA - 2010 Y2 - 2022/4/30 PB - The MIT Press AB - We develop a new estimator of the number of factors in the approximate factor models. The estimator works well even when the idiosyncratic terms are substantially correlated. It is based on the fact, established in the paper, that any finite number of the largest "idiosyncratic" eigenvalues of the sample covariance matrix cluster around a single point. In contrast, all the "systematic" eigenvalues, the number of which equals the number of factors, diverge to infinity. The estimator consistently separates the diverging eigenvalues from the cluster and counts the number of the separated eigenvalues. We consider a macroeconomic and a financial application. SN - 0034-6535 UR - http://www.jstor.org/stable/40985808 ER - TY - JOUR AU - Bai, Jushan AU - Ng, Serena TI - Determining the Number of Primitive Shocks in Factor Models T2 - Journal of Business & Economic Statistics VL - 25 IS - 1 SP - 52-60 PY - 2007 DA - 2007 Y2 - 2022/4/30 PB - [American Statistical Association, Taylor & Francis, Ltd.] AB - A widely held but untested assumption underlying macroeconomic analysis is that the number of shocks driving economic fluctuations, q, is small. In this article we associate q with the number of dynamic factors in a large panel of data. We propose a methodology to determine q without having to estimate the dynamic factors. We first estimate a VAR in r static factors, where the factors are obtained by applying the method of principal components to a large panel of data, then compute the eigenvalues of the residual covariance or correlation matrix. We then test whether their eigenvalues satisfy an asymptotically shrinking bound that reflects sampling error. We apply the procedure to determine the number of primitive shocks in a large number of macroeconomic time series. An important aspect of the present analysis is to make precise the relationship between the dynamic factors and the static factors, which is a result of independent interest. SN - 0735-0015 UR - http://www.jstor.org/stable/27638906 ER - TY - JOUR AU - Stock, James H AU - Watson, Mark W TI - New Indexes of Coincident and Leading Economic Indicators T2 - NBER Macroeconomics Annual VL - 4 SP - 351-394 PY - 1989 DA - 1989 AB - The system of Leading and Coincident Economic Indicators, currently maintained by the U.S. Department of Commerce (DOC), was developed as part of the NBER research program on business cycles over fifty years ago. This paper uses recent developments in econometric methodology and computing technology to take a fresh look at this system. The result is three experimental indexes. The first, constructed using a dynamic factor model, is numerically similar to the current index of coincident indicators maintained by the DOC. The second, an alternative index of leading indicators, is designed to forecast the growth in the DOC index over a six month horizon. The third-a "Recession Index"-estimates the probability that the economy will be in a recession six months hence. Only two of the seven series in the proposed leading index are used by the DOC to construct their index. Of these new series, interest rates (a public-private risk premium and the slope of the yield curve) are found to be part SN - 0889-3365 UR - https://search-ebscohost-com.ez.urosario.edu.co/login.aspx?direct=true&AuthType=ip&db=edsjsr&AN=edsjsr.10.2307.3584985&lang=es&site=eds-live&scope=site KW - Economic indices, Economic recessions, Economic indicators, Index of Leading Economic Indicators, Economic fluctuations, Economic growth rate, Gross national product, Macroeconomics, Stock market indices, Inventories ER - TY - JOUR AU - Gordon, Robert J TI - Price Inertia and Policy Ineffectiveness in the United States, 1890-1980 T2 - Journal of Political Economy VL - 90 IS - 6 SP - 1087-1117 PY - 1982 DA - 1982 AB - This paper introduces a new approach to the empirical testing of the Lucas-Sargent-Wallace (LSW) "policy ineffectiveness proposition," which compares the LSW hypothesis with an alternative that states that prices respond fully in the long run, but only gradually in the short run, to nominal aggregate demand disturbances. The empirical equations, estimated for a new set of quarterly data extending back to 1890, exhibit uniformly high responses of real output and low responses of price changes to anticipated changes in nominal GNP. The paper compares and tests three alternative methods of introducing "persistence effects" into the LSW framework. SN - 0022-3808 UR - https://search-ebscohost-com.ez.urosario.edu.co/login.aspx?direct=true&AuthType=ip&db=edsjsr&AN=edsjsr.1830940&lang=es&site=eds-live&scope=site KW - Coefficients, Gross national product, Price changes, Variable coefficients, Real output, Political economy, Demand change, Price level changes, Nominal prices, Velocity ER - TY - JOUR AU - Stock, James H AU - Watson, Mark W TI - Forecasting inflation T2 - Journal of Monetary Economics VL - 44 IS - 2 SP - 293-335 PY - 1999 DA - 1999 AB - This paper investigates forecasts of US inflation at the 12-month horizon. The starting point is the conventional unemployment rate Phillips curve, which is examined in a simulated out-of-sample forecasting framework. Inflation forecasts produced by the Phillips curve generally have been more accurate than forecasts based on other macroeconomic variables, including interest rates, money and commodity prices. These forecasts can however be improved upon using a generalized Phillips curve based on measures of real aggregate activity other than unemployment, especially a new index of aggregate activity based on 168 economic indicators. SN - 0304-3932 DO - 10.1016/S0304-3932(99)00027-6 UR - https://www.sciencedirect.com/science/article/pii/S0304393299000276 UR - http://dx.doi.org/10.1016/S0304-3932(99)00027-6 KW - Phillips curve, Forecast combination ER - TY - BOOK AU - Box, George E P TI - Time series analysis: forecasting and control T2 - Wiley series in probability and statistics PY - 2008 DA - 2008 PB - John Wiley SN - 9780470272848 UR - https://search-ebscohost-com.ez.urosario.edu.co/login.aspx?direct=true&AuthType=ip&db=edshlc&AN=edshlc.011534628.7&lang=es&site=eds-live&scope=site ER - TY - JOUR AU - Bikker, J A TI - Inflation forecasting for aggregates of the EU-7 and EU-14 with Bayesian VAR models T2 - Journal of Forecasting VL - 17 IS - n2 PY - 1998 DA - 1998 AB - Key economic aggregates of the EU-7 and the EU-14 are analyzed using the Bayesian Vector Auto-Regressive (BVAR) model as a forecasting tool. Using absolute forecasting performance and comparing ex-post BVAR forecasts with OECD forecasts, the BVAR model proves useful as a forecasting tool in addition to structural macroeconomic models. It is revealed that forecast errors are strongly influenced by pooling when aggregate models are compared to single-country models. SN - 0277-6693 UR - https://search-ebscohost-com.ez.urosario.edu.co/login.aspx?direct=true&AuthType=ip&db=edsbig&AN=edsbig.A20560301&lang=es&site=eds-live&scope=site KW - European Union -- Economic aspects, Inflation (Finance) -- Forecasts and trends, Economic forecasting -- Models ER - TY - JOUR AU - Stelmasiak, Damian AU - Szafrański, Grzegorz TI - Forecasting the Polish Inflation Using Bayesian VAR Models with Seasonality T2 - Central European Journal of Economic Modelling & Econometrics VL - 8 IS - 1 SP - 21-42 PY - 2016 DA - 2016 AB - Bayesian VAR (BVAR) models offer a practical solution to the parameter proliferation concerns as they allow to introduce a priori information on seasonality and persistence of inflation in a multivariate framework. We investigate alternative prior specifications in the case of time series with a clear seasonal pattern. In the empirical part we forecast the monthly headline inflation in the Polish economy over the period 2011-2014 employing two popular BVAR frameworks: a steady-state reduced-form BVAR and just-identified structural BVAR model. To evaluate the forecast performance we use the pseudo realtime vintages of timely information from consumer and financial markets. We compare different models in terms of both point and density forecasts. Using formal testing procedure for density-based scores we provide the empirical evidence of superiority of the steady-state BVAR specifications with tight seasonal priors. [ABSTRACT FROM AUTHOR] SN - 2080-0886 UR - https://search-ebscohost-com.ez.urosario.edu.co/login.aspx?direct=true&AuthType=ip&db=bth&AN=114598098&lang=es&site=eds-live&scope=site KW - Price inflation, Economic forecasting, Bayesian analysis, Financial markets, Vector autoregression model, Bayesian VAR models, density-based scores, forecasting inflation, seasonality ER - TY - JOUR AU - Medel, Carlos A TI - Forecasting Inflation with the Hybrid New Keynesian Phillips Curve: A Compact-Scale Global VAR Approach PY - 2018 DA - 2018 AB - In this article, it is analysed the multihorizon predictive power of the Hybrid New Keynesian Phillips Curve (HNKPC) making use of a compact-scale Global VAR for the headline inflation of six developed countries with different inflationary experiences; covering from 2000.1 until 2014.12. The key element of this article is the use of direct measures of inflation expectations--Consensus Economics--embedded in a Global VAR environment, i.e. modelling cross-country interactions. The Global VAR point forecast is evaluated using the Mean Squared Forecast Error (MSFE) statistic and statistically compared with several benchmarks. These belong to traditional statistical modelling, such as autoregressions (AR), the exponential smoothing model (ES), and the random walk model (RW). One last economics-based benchmark is the closed economy univariate HNKPC. The results indicate that the Global VAR is a valid forecasting procedure especially for the short-run. The most accurate forecasts, however, a UR - https://search-ebscohost-com.ez.urosario.edu.co/login.aspx?direct=true&AuthType=ip&db=edsair&AN=edsair.doi.dedup.....48c9694be115e874b6f970f1edd731ba&lang=es&site=eds-live&scope=site KW - General Economics, Econometrics and Finance, Inflation, media_common.quotation_subject, media_common, New Keynesian economics, Univariate, Statistic, Deflation, Economics, Exponential smoothing, Phillips curve, Econometrics, Headline inflation, jel:C22, jel:C26, jel:C53, jel:E31, jel:E37, jel:E47, New Keynesian Phillips Curve, inflation forecasts, out-of-sample comparisons, survey data, Global VAR, time-series models ER - TY - JOUR AU - Bvuchete, Munyaradzi AU - Grobbelaar, Sara Saartjie AU - van Eeden, Joubert TI - A Network Maturity Mapping Tool for Demand-Driven Supply Chain Management: A Case for the Public Healthcare Sector T2 - Sustainability (2071-1050) VL - 13 IS - 21 SP - 11988 PY - 2021 DA - 2021 AB - The healthcare supply chain is a complex adaptive ecosystem that facilitates the delivery of health products to the end patient in a cost-effective way. However, low forecast accuracy and high demand volatility in healthcare supply chains have resulted in an increase in stockouts, operational inefficiencies, poor health outcomes, and a significant increase in supply chain costs. To cope with these challenges, organisations are trying to adopt demand-driven supply chain management (DDSCM) operating practices which have been established in other sectors such as the telecommunications, fruit, and flower industries. However, previous studies have not considered these practices in the healthcare industry, and hence no methodologies exist that support the implementation of these practices in this context. Moreover, current studies present cases where the focus has been on improving and expanding individual organisational performance, but no supply chain network-level studies exist on the he SN - 2071-1050 UR - https://search-ebscohost-com.ez.urosario.edu.co/login.aspx?direct=true&AuthType=ip&db=edb&AN=153601380&lang=es&site=eds-live&scope=site KW - demand-driven supply chain management, maturity models, product classification, public healthcare supply chains, segmentation ER - TY - CPAPER AU - Wu, Shin-Fu AU - Chang, Chia-Yung AU - Lee, Shie-Jue TI - Time Series Forecasting with Missing Values VL - 1 PY - 2015 DA - 2015 DO - 10.4108/icst.iniscom.2015.258269 UR - http://dx.doi.org/10.4108/icst.iniscom.2015.258269 ER - TY - JOUR AU - Rubin, Donald B TI - Inference and Missing Data T2 - Biometrika VL - 63 IS - 3 SP - 581-592 PY - 1976 DA - 1976 Y2 - 2022/5/1 PB - [Oxford University Press, Biometrika Trust] AB - When making sampling distribution inferences about the parameter of the data, θ, it is appropriate to ignore the process that causes missing data if the missing data are `missing at random' and the observed data are `observed at random', but these inferences are generally conditional on the observed pattern of missing data. When making direct-likelihood or Bayesian inferences about θ, it is appropriate to ignore the process that causes missing data if the missing data are missing at random and the parameter of the missing data process is `distinct' from θ. These conditions are the weakest general conditions under which ignoring the process that causes missing data always leads to correct inferences. SN - 0006-3444 UR - http://www.jstor.org/stable/2335739 ER - TY - JOUR AU - Rubin, Donald B TI - Multiple Imputation After 18+ Years T2 - Journal of the American Statistical Association VL - 91 IS - 434 SP - 473-489 PY - 1996 DA - 1996 Y2 - 2022/5/1 PB - [American Statistical Association, Taylor & Francis, Ltd.] AB - Multiple imputation was designed to handle the problem of missing data in public-use data bases where the data-base constructor and the ultimate user are distinct entities. The objective is valid frequency inference for ultimate users who in general have access only to complete-data software and possess limited knowledge of specific reasons and models for nonresponse. For this situation and objective, I believe that multiple imputation by the data-base constructor is the method of choice. This article first provides a description of the assumed context and objectives, and second, reviews the multiple imputation framework and its standard results. These preliminary discussions are especially important because some recent commentaries on multiple imputation have reflected either misunderstandings of the practical objectives of multiple imputation or misunderstandings of fundamental theoretical results. Then, criticisms of multiple imputation are considered, and, finally, comparisons are made to alternative strategies. SN - 0162-1459 UR - http://www.jstor.org/stable/2291635 ER - TY - JOUR AU - Meng, Xiao-Li TI - Multiple-Imputation Inferences with Uncongenial Sources of Input T2 - Statistical Science VL - 9 IS - 4 SP - 538-558 PY - 1994 DA - 1994 Y2 - 2022/5/1 PB - Institute of Mathematical Statistics AB - Conducting sample surveys, imputing incomplete observations, and analyzing the resulting data are three indispensable phases of modern practice with public-use data files and with many other statistical applications. Each phase inherits different input, including the information preceding it and the intellectual assessments available, and aims to provide output that is one step closer to arriving at statistical inferences with scientific relevance. However, the role of the imputation phase has often been viewed as merely providing computational convenience for users of data. Although facilitating computation is very important, such a viewpoint ignores the imputer's assessments and information inaccessible to the users. This view underlies the recent controversy over the validity of multiple-imputation inference when a procedure for analyzing multiply imputed data sets cannot be derived from (is "uncongenial" to) the model adopted for multiple imputation. Given sensible imputations and complete-data analysis procedures, inferences from standard multiple-imputation combining rules are typically superior to, and thus different from, users' incomplete-data analyses. The latter may suffer from serious nonresponse biases because such analyses often must rely on convenient but unrealistic assumptions about the nonresponse mechanism. When it is desirable to conduct inferences under models for nonresponse other than the original imputation model, a possible alternative to recreating imputations is to incorporate appropriate importance weights into the standard combining rules. These points are reviewed and explored by simple examples and general theory, from both Bayesian and frequentist perspectives, particularly from the randomization perspective. Some convenient terms are suggested for facilitating communication among researchers from different perspectives when evaluating multiple-imputation inferences with uncongenial sources of input. SN - 0883-4237 UR - http://www.jstor.org/stable/2246252 ER - TY - BOOK AU - Little, R J A AU - Rubin, D B TI - Statistical Analysis With Missing Data T2 - Wiley Series in Probability and Statistics PY - 1987 DA - 1987 PB - Wiley SN - 9780471802549 UR - https://books.google.com.co/books?id=w40QAQAAIAAJ ER - TY - BOOK AU - Schafer, J L TI - Analysis of Incomplete Multivariate Data T2 - Chapman & Hall/CRC Monographs on Statistics & Applied Probability PY - 1997 DA - 1997 PB - CRC Press SN - 9781439821862 UR - https://books.google.com.co/books?id=3TFWRjn1f-oC ER - TY - BOOK AU - Carpenter, J AU - Kenward, M TI - Multiple Imputation and its Application T2 - Statistics in Practice PY - 2013 DA - 2013 PB - Wiley SN - 9780470740521 UR - https://books.google.com.co/books?id=pB98Pbee4-0C ER - TY - JOUR AU - Serge, Demeyer AU - Daiane, de Mattos AU - Ferreira, Pedro Guilherme Costa TI - Nowcasting: An R Package for Predicting Economic Variables Using Dynamic Factor Models T2 - R J. VL - 11 SP - 230 PY - 2019 DA - 2019 ER - TY - CPAPER AU - Yaffee, Robert TI - Forecast evaluation using Stata PY - 2010 DA - 2010 ER - TY - JOUR AU - Diebold, 2 ), F.X. ( 1 AU - Mariano, R S ( 3 ) TI - Comparing predictive accuracy T2 - Journal of Business and Economic Statistics VL - 13 IS - 3 SP - 253-263 PY - 1995 DA - 1995 SN - 1537-2707 UR - https://search-ebscohost-com.ez.urosario.edu.co/login.aspx?direct=true&AuthType=ip&db=edselc&AN=edselc.2-52.0-68249136965&lang=es&site=eds-live&scope=site KW - Economic loss function, Exchange rates, Forecast evaluation, Forecasting, Nonparametric tests, Sign test ER - TY - JOUR AU - Tjalling C., Koopmans TI - The Klein-Goldberger Forecasts for 1951, 1952 and 1954, Compared with Naive-Model Forecasts T2 - Cowles Foundation Discussion Papers PY - 1956 DA - 1956 AB - No abstract is available for this item. UR - https://search-ebscohost-com.ez.urosario.edu.co/login.aspx?direct=true&AuthType=ip&db=edsrep&AN=edsrep.p.cwl.cwldpp.12&lang=es&site=eds-live&scope=site ER - TY - JOUR AU - Lev, Baruch TI - Testing a Prediction Method for Multivariate Budgets T2 - Journal of Accounting Research (Wiley-Blackwell) VL - 7 IS - 3 SP - 182-197 PY - 1969 DA - 1969 AB - This paper reports an empirical test of the usefulness of a prediction method for multivariate budgets suggested by Theil. The method, based on information theory concepts, is described in the first three sections, and results of the test are presented in the remaining sections. These results show that the suggested prediction method outperforms both the actual forecasts made by the firms who provided the data and two naive forecasts. [ABSTRACT FROM AUTHOR] SN - 0021-8456 UR - https://search-ebscohost-com.ez.urosario.edu.co/login.aspx?direct=true&AuthType=ip&db=edb&AN=6415767&lang=es&site=eds-live&scope=site KW - MULTIVARIATE analysis, BUDGET, INFORMATION theory, MATHEMATICAL statistics, ANALYSIS of variance, THEIL, H. ER - TY - JOUR AU - Richards, R Malcolm AU - Benjamin, James J AU - Strawser, Robert H TI - An Examination of the Accuracy of Earnings Forecasts T2 - Financial Management VL - 6 IS - 3 SP - 78-86 PY - 1977 DA - 1977 AB - This paper provides additional information regarding the usefulness of the corporate earnings forecasts of analysts. The accuracy of such forecasts is evaluated by comparing them to the accuracy of forecasts generated by "naive" mechanical models. Additionally, forecast errors are studied for various industries. SN - 0046-3892 UR - https://search-ebscohost-com.ez.urosario.edu.co/login.aspx?direct=true&AuthType=ip&db=edsjsr&AN=edsjsr.3665260&lang=es&site=eds-live&scope=site KW - Earnings forecasting, Analytical forecasting, Forecasting models, Modeling, Time series forecasting, Statistical forecasts, Employment forecasting, Banking industry, Investors, Corporations ER - TY - JOUR AU - Charles H., Brandon AU - Jeffrey E., Jarrett AU - Saleha B., Khumawala TI - Note---Revising Forecasts of Accounting Earnings: A Comparison with the Box-Jenkins Method T2 - Management Science IS - 2 SP - 256 PY - 1983 DA - 1983 AB - The purpose of this study was to contribute to the literature concerning forecasting the time series of accounting earnings. To accomplish this objective an experiment was conducted to compare the performance of Theil's Optimal Linear Correction technique for revising quarterly Box-Jenkins and other naive model forecasts of accounting earnings against the unrevised forecasts. Several results of this study are of particular interest. First, the study indicated that the Watts-Griffin parsimonious model outperformed other firm specific Box-Jenkins models. Second, the Optimal Linear Correction produced revised forecasts that were uniformly more accurate than the original unadjusted forecasts. Finally, the naive extrapolative time series models outperformed Box-Jenkins forecasts of accounting earnings. UR - https://search-ebscohost-com.ez.urosario.edu.co/login.aspx?direct=true&AuthType=ip&db=edsrep&AN=edsrep.a.inm.ormnsc.v29y1983i2p256.263&lang=es&site=eds-live&scope=site KW - forecasting applications: arima processes ER - TY - JOUR AU - Lindsay I., Hogan AU - Peter J., Urban AU - V. V., Anh TI - A Vector Autoregressive Forecasting Model of The US$/$A Exchange Rate T2 - Australian Journal of Management IS - 2 SP - 47 PY - 1985 DA - 1985 AB - A forecasting model of the US$/$A exchange rate is derived through the application of vector autoregression (VAR) techniques. The major theoretical models of exchange rate determination are reviewed to identify relevant variables to include in the VAR model. For the within-sample period of September 1974 to May 1983, the VAR forecasts are found to be clearly superior to the naive no-charge extrapolated forecasts. However, the position is reversed when the out-of-sample forecasts are examined. UR - https://search-ebscohost-com.ez.urosario.edu.co/login.aspx?direct=true&AuthType=ip&db=edsrep&AN=edsrep.a.sae.ausman.v10y1985i2p47.65&lang=es&site=eds-live&scope=site KW - VECTOR AUTOREGRESSIVE MODEL, EXCHANGE RATE, AUSTRALIA, USA ER - TY - JOUR AU - Fabio, Rumler AU - Maria Teresa, Valderrama TI - Comparing the New Keynesian Phillips Curve with time series models to forecast inflation T2 - The North American Journal of Economics and Finance VL - 21 SP - 126-144 PY - 2008 DA - 2008 AB - The New Keynesian Phillips Curve, as a structural model of inflation dynamics, has mostly been used to explain past inflation developments, but has hardly been used for forecasting purposes. We propose a method of forecasting inflation based on the present-value formulation of the hybrid New Keynesian Phillips Curve. To evaluate the forecasting performance of this model we compare it with forecasts generated from a traditional Phillips Curve and time series models at different forecast horizons. As state-of-the-art time series models used in forecasting we employ a Bayesian VAR, a conventional VAR and a simple autoregressive model. We find that the New Keynesian Phillips Curve delivers relatively more accurate forecasts of inflation in Austria compared to the other models for longer forecast horizons (more than 3 months) while they are outperformed by the time series models only for the very short forecast horizon. This is consistent with the finding in the literature that structural SN - 1062-9408 UR - https://search-ebscohost-com.ez.urosario.edu.co/login.aspx?direct=true&AuthType=ip&db=edsair&AN=edsair.doi.dedup.....b527f8fca4a142f6ac475cf32f37172a&lang=es&site=eds-live&scope=site KW - Economics and Econometrics, Finance, Inflation, media_common.quotation_subject, media_common, Economics, Autoregressive model, Bayesian vector autoregression, Econometrics, Phillips curve, New Keynesian economics, jel:E31, jel:C32, jel:C53, New Keynesian Phillips Curve, Inflation Forecasting, Forecast Evaluation, Bayesian VAR, Physics::Atmospheric and Oceanic Physics, General Relativity and Quantum Cosmology ER - TY - JOUR AU - Arruda, Elano Ferreira AU - Ferreira, Roberto Tatiwa AU - Castelar, Ivan TI - Modelos Lineares e Não Lineares da Curva de Phillips para Previsão da Taxa de Inflação no Brasil T2 - Revista Brasileira de Economia - RBE IS - 3 PY - 2011 DA - 2011 AB - This paper compares forecasts of Brazilian monthly inflation rate generated from different linear and nonlinear time series and Phillips’ curve models. In general, the nonlinear models had a better performance. The VAR model produced the smallest mean square forecast error (MSE) among linear models, while overall best forecasts were generated by the extended Phillips curve with a threshold effect, which presented a 20% smaller MSE than the VAR model. The Diebold e Mariano (1995) test indicated a significant difference between forecasts generated from the VAR and the expanded Phillips curve with a threshold. UR - https://search-ebscohost-com.ez.urosario.edu.co/login.aspx?direct=true&AuthType=ip&db=edsrep&AN=edsrep.a.fgv.epgrbe.v65y2011i3a1523&lang=es&site=eds-live&scope=site ER - TY - JOUR AU - Fanelli, Luca TI - Evaluating the New Keynesian Phillips Curve under VAR-based learning T2 - MPRA Paper PY - 2007 DA - 2007 AB - This paper proposes the evaluation of the New Keynesian Phillips Curve (NKPC) under a new learning mechanism where VAR learning dynamics is combined with the idea of testing the validity of the forward-looking model of inflation dynamics. The key assumption is that agents’ perceived law of motion is a VAR whose parameters are updated by recursive least squares. Differently from standard adaptive learning methods, agents test sequentially the cross-equation restrictions that the NKPC imposes on the VAR as the information set increases. When the restrictions are not rejected agents learn under the restricted system and exploit the cross-equation restrictions to forecast inflation. It is thus possible to check how much and in which periods agents’ beliefs are consistent with the restrictions of the theory. The empirical analysis on quarterly data on the euro area shows that the NKPC with negligible backward-looking parameter is not rejected when the model is evaluated over the period 198 UR - https://search-ebscohost-com.ez.urosario.edu.co/login.aspx?direct=true&AuthType=ip&db=edsrep&AN=edsrep.p.pra.mprapa.1616&lang=es&site=eds-live&scope=site KW - Adaptive learning, Cross-equation restrictions, Forward-looking model of inflation dynamics, Perceived Law of Motion, Recursive Least Squares, VAR ER - TY - JOUR AU - Camba-Mendez, Gonzalo AU - Kapetanios, George AU - Smith, Richard J AU - Weale, Martin R TI - An automatic leading indicator of economic activity: forecasting GDP growth for European countries T2 - The Econometrics Journal VL - 4 IS - 1 SP - S56-S90 PY - 2001 DA - 2001 Y2 - 2022/5/13 PB - [Royal Economic Society, Wiley] AB - In the construction of a leading indicator model of economic activity, economists must select among a pool of variables which lead output growth. Usually the pool of variables is large and a selection of a subset must be carried out. This paper proposes an automatic leading indicator model which, rather than preselection, uses a dynamic factor model to summarize the information content of a pool of variables. Results using quarterly data for France, Germany, Italy and the United Kingdom show that the overall forecasting performance of the automatic leading indicator model appears better than that of more traditional VAR and BVAR models. SN - 1368-4221 UR - http://www.jstor.org/stable/23114939 ER -