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Dissertations / Theses on the topic 'GDP Forecasting'

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Published: 4 June 2021
Last updated: 18 February 2022

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1

Björnfot, Fredrik. "GDP Growth Rate Nowcasting and Forecasting." Thesis, Umeå universitet, Institutionen för fysik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-132951.

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The main purpose of this project was to help Swedbank get a better understandingof how gross domestic product growth rate develops in the future froma data set of macroeconomic variables. Since GDP values are released long aftera quarter has ended Swedbank would like to have a model that could predictupcoming GDP from these data sets. This was solved by a combination ofgrowth rate predictions from a dynamic factor model, a vector autoregressivemodel and two machine learning models. The predictions were combined usinga weighting method called system averaging model where the model predictionwit
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Lindgren, Hanna, and Victor Nilsson. "MIDAS : Forecasting quarterly GDP using higher-frequency data." Thesis, Uppsala universitet, Statistiska institutionen, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-242554.

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We forecast US GDP sampled quarterly over horizons ranging from one quarter to three years. Using AR-MIDAS models we study three lag polynomials: the Almon lag, the exponential Almon lag and the beta lag, and nine macroeconomic variables, sampled weekly or monthly. Our benchmark model is an AR(1) and we compare forecast errors using RMSE. In all instances the AR-MIDAS achieves lower forecast errors compared to the benchmark model. The predictor sampled weekly generally performs better compared to other predictors, which are sampled monthly.
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Naser, Hanan. "An econometric investigation of forecasting GDP, oil prices, and relationships among GDP and energy sources." Thesis, University of Sheffield, 2014. http://etheses.whiterose.ac.uk/7041/.

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In order for a policy to be effective, the links between the policy tools and the sub- sequent targets must be known, understandable, stable, and predictable. In this respect, this thesis is composed of three separate yet related empirical studies, that target important macroeconomic variables, which play a central role in the conduct of macroeconomic policies. First, simple regression estimates and a factor-based model are utilized to produce forecasts for Bahrain quarterly GDP growth using quarterly data-set that cover the period from 1995: Q1 to 2008: Q3. To do so, we run a simple regressio
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4

Pilström, Patrick, and Sebastian Pohl. "Forecasting GDP Growth : The Case of The Baltic States." Thesis, Jönköping University, JIBS, Economics, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-9776.

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<p>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.</p><p>The performed forecasts have provided good results for horizons up to t+8. The forecasts for 2009 (t+12) are in line with thos
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Campos, Claúdia Cristina Marinho. "Predicting GDP growth in the Euro Area." Master's thesis, NSBE - UNL, 2013. http://hdl.handle.net/10362/9837.

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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics<br>Predicting GDP growth is a concern of several economic agents. The right way to model such variable is far from consensual. This paper’s goal is to compare different models for GDP growth forecasting in the euro area. For comparative purposes, an autoregressive model (which is used as benchmark) and two Autoregressive Distributed Models (ADL), which contain financial and non-financial variables, chosen based on the literature, are used. The main
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6

Mattos, Pedro Montero. "Nowcasting Brazilian GDP." reponame:Repositório Institucional do FGV, 2017. http://hdl.handle.net/10438/18775.

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Submitted by Pedro Montero Mattos (pmattos90@gmail.com) on 2017-09-05T14:09:34Z No. of bitstreams: 1 nowcasting-brazilian-gdp-ficha.pdf: 808279 bytes, checksum: 3b790fa6a2be106b618a354ab1f18650 (MD5)<br>Rejected by Joana Martorini (joana.martorini@fgv.br), reason: Prezado Pedro, boa noite, Seu trabalho não condiz com as normas necessárias para aprovação. Favor corrigir para que possamos aceitar o arquivo. Na capa faltou o nome completo da Escola, e ao identificar o local, na parte inferior da página, colocar somente o nome da cidade e o ano, retirar páginas em branco. Dissertação, banc
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Chen, Yu. "FORECASTING WITH MIXED FREQUENCY DATA:MIDAS VERSUS STATE SPACE DYNAMIC FACTOR MODEL : AN APPLICATION TO FORECASTING SWEDISH GDP GROWTH." Thesis, Örebro universitet, Handelshögskolan vid Örebro Universitet, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-29475.

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Most macroeconomic activity series such as Swedish GDP growth are collected quarterly while an important proportion of time series are recorded at a higher frequency. Thus, policy and business decision makers are often confront with the problems of forecasting and assessing current business and economy state via incomplete statistical data due to publication lags. In this paper, we survey a few general methods and examine different models for mixed frequency issues. We mainly compare mixed data sampling regression (MIDAS) and state space dynamic factor model (SS-DFM) by the comparison experime
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8

Enocksson, David. "Forecasting Swedish Output Growth: : An Empirical Comparison of MIDAS Regressions and theRAMSES Model." Thesis, Uppsala universitet, Statistiska institutionen, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-195873.

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This thesis compares MIDAS regressions, introduced in Ghysels, Santa-Clara and Valkanov (2002), to the RAMSES model, used by the Riksbank,in forecasting Swedish quarterly output growth (GDP). Using Swedish GPDdata from 1993Q1 and onwards, we compare forecasts for the period 2010Q1to 2011Q4, and we show that for longer forecast horizons (commonly usedby the Riksbank for monetary policy decisions), such as two and three yearsahead in time, the MIDAS regressions clearly outperforms the RAMSESmodel. For shorter horizons the results are not conclusive.KEYWORDS: MIDAS, GDP, forecasting, Sveriges Rik
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9

Adriansson, Nils, and Ingrid Mattsson. "Forecasting GDP Growth, or How Can Random Forests Improve Predictions in Economics?" Thesis, Uppsala universitet, Statistiska institutionen, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-243028.

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GDP is used to measure the economic state of a country and accurate forecasts of it is therefore important. Using the Economic Tendency Survey we investigate forecasting quarterly GDP growth using the data mining technique Random Forest. Comparisons are made with a benchmark AR(1) and an ad hoc linear model built on the most important variables suggested by the Random Forest. Evaluation by forecasting shows that the Random Forest makes the most accurate forecast supporting the theory that there are benefits to using Random Forests on economic time series.
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10

Lundberg, Otto. "GDP forecasting and nowcasting : Utilizing a system for averaging models to improve GDP predictions for six countries around the world." Thesis, Umeå universitet, Institutionen för matematik och matematisk statistik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-131718.

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This study was issued by Swedbank because they wanted too improve their GDP growth forecast capabilites.  A program was developed and tested on six countries; USA, Sweden, Germany, UK, Brazil and Norway. In this paper I investigate if I can reduce forecasting error for GDP growth by taking a smart average from a variety of models compared to both the best individual models and a random walk. I combine the forecasts from four model groups: Vector autoregression, principal component analysis, machine learning and random walk. The smart average is given by a system that give more weight to the pr
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11

Ferreira, Roberto Tatiwa. "Forecasting Quarterly Brazilian Gdp Growth Rate With Linear and Nonlinear Diffusion Index Models." Universidade Federal do CearÃ, 2005. http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=1294.

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CoordenaÃÃo de AperfeiÃoamento de Pessoal de NÃvel Superior<br>The present study uses linear and non-linear diffusion index models to produce one-stepahead forecast of quarterly Brazilian GDP growth rate. Diffusion index models are like dynamic factors models. These factors are latent variables that represent a common property from the explanatory variables, then allowing a considerably reduction of its number in econometric models elaborated to attend the main objective of this work. The non-linear diffusion index models used in this thesis are not only parsimonious ones, but also they try to
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12

Bauch, Jacob H. "The Impact of Oil Prices on the U.S. Economy." Scholarship @ Claremont, 2011. http://scholarship.claremont.edu/cmc_theses/146.

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Nine of the ten recessions since WWII have been preceded by relatively large and sudden increases in the price of oil. In this paper, I use time series analysis to forecast GDP growth using oil prices. I use the methodology from Hamilton (2009), and extend the dataset through 2010. Impulse response functions are used to analyze the historical performance of the model’s one-year-ahead forecasts. In April, 2011, the International Monetary Fund changed its forecast of 2011 GDP growth in the U.S. from 3.0% to 2.8% largely due to persistently high oil prices. My model suggests that the price increa
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13

Ferreira, Roberto Tatiwa. "Forecasting quarterly brazilian GDP growth rate with linear and non linear diffusion inex models." reponame:Repositório Institucional da UFC, 2005. http://www.repositorio.ufc.br/handle/riufc/659.

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FERREIRA, Roberto Tatiwa. Forecasting quarterly brazilian GDP growth rate with linear and nonlinear diffusion index models. Tese (Doutorado). Universidade Federal do Ceará, Programa de Pós Graduação em Economia, CAEN, Fortaleza, 2005.<br>Submitted by Mônica Correia Aquino (monicacorreiaaquino@gmail.com) on 2011-08-12T20:16:58Z No. of bitstreams: 1 Tese_de_Roberto_Tatiwa_Ferreira_seguro_2011[1].pdf: 608496 bytes, checksum: b91e1027e0c3b1ca6eb0f0ad3ec02e3f (MD5)<br>Approved for entry into archive by Mônica Correia Aquino(monicacorreiaaquino@gmail.com) on 2011-08-12T20:17:14Z (GMT) No. of bitst
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14

Eklund, Jana. "Essays on forecasting and Bayesian model averaging." Doctoral thesis, Handelshögskolan i Stockholm, Ekonomisk Statistik (ES), 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:hhs:diva-490.

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This thesis, which consists of four chapters, focuses on forecasting in a data-rich environment and related computational issues. Chapter 1, “An embarrassment of riches: Forecasting using large panels” explores the idea of combining forecasts from various indicator models by using Bayesian model averaging (BMA) and compares the predictive performance of BMA with predictive performance of factor models. The combination of these two methods is also implemented, together with a benchmark, a simple autoregressive model. The forecast comparison is conducted in a pseudo out-of-sample framework for t
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15

Duarte, Cláudia Filipa Pires. "Essays on mixed-frequency data : forecasting and unit root testing." Doctoral thesis, Instituto Superior de Economia e Gestão, 2016. http://hdl.handle.net/10400.5/11662.

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Doutoramento em Economia<br>Nas últimas décadas, OS investigadores têm tido acesso a bases de dados cada vez mais abrangentes, que incluem séries com frequências temporais mais elevadas e que são divulgadas mais atempadamente. Em contraste, algumas variáveis, nomeadamente alguns dos principais indicadores macroeconómicos, são divulgados com urn desfasamento temporal significativo e com baixa frequência. Esta situação levanta questões sobre como lidar com séries com frequências temporais diferentes, mistas. Ao longo do tempo, várias técnicas têm sido propostas. Esta tese debruça-se sobre uma t
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16

Gaberšek, Saša. "The dynamics of gap flow over idealized topography /." Thesis, Connect to this title online; UW restricted, 2002. http://hdl.handle.net/1773/10098.

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17

PARNES, ILAN SAMPAIO. "UNCERTAINTY MEASURES AND THEIR IMPACTS ON FORECASTING THE BRAZILIAN OUTPUT GAP." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2018. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=35932@1.

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A incerteza é um fator relevante na modelagem de variáveis macroeconômi-cas, especialmente em países emergentes. Neste estudo, tentamos entender se me-didas de incerteza oriundas do mercado brasileiro podem melhorar as projeções de PIB do país. Traçando uma curva IS da forma mais simples possível: relacionando o hiato do produto a suas primeiras defasagens e aos juros reais ex-ante, podemos adicionar medidas de incerteza e atestar se estas melhoram as projeções de hiato realizadas para o período imediatamente subsequente. Como medidas de incerte-za, utilizamos a dispersão de expectativas do bo
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18

de, Rezende Rafael B. "Essays on Macro-Financial Linkages." Doctoral thesis, Handelshögskolan i Stockholm, Institutionen för Finansiell ekonomi, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:hhs:diva-2259.

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This doctoral thesis is a collection of four papers on the analysis of the term structure of interest rates with a focus at the intersection of macroeconomics and finance. "Risk in Macroeconomic Fundamentals and Bond Return Predictability" documents that factors related to risks underlying the macroeconomy such as expectations, uncertainty and downside (upside) macroeconomic risks are able to explain variation in bond risk premia. The information provided is found to be, to a large extent, unrelated to that contained in forward rates and current macroeconomic conditions. "Out-of-sample bond ex
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19

Duarte, Yury Catalani Nepomuceno. "Modelos de simulação da cultura do milho - uso na determinação das quebras de produtividade (Yield Gaps) e na previsão de safra da cultura no Brasil." Universidade de São Paulo, 2018. http://www.teses.usp.br/teses/disponiveis/11/11152/tde-15052018-104958/.

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Sendo o cereal mais produzido no mundo e em larga expansão, os sistemas de produção de milho são altamente complexos e sua produção é diretamente dependente de fatores ligados tanto ao clima local quanto ao manejo da cultura. Para auxiliar na determinação tanto dos patamares produtivos de milho quanto quantificar o impacto causado por condições adversas tanto de clima quanto de manejo, pode-se lançar mão do uso de modelos de simulação de culturas. Para que os modelos possam ser devidamente aplicados, uma base solida de dados meteorológicos deve ser consistida, a fim de alimentar esses modelos.
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Cusinato, Rafael Tiecher. "Ensaios sobre previsão de inflação e análise de dados em tempo real no Brasil." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2009. http://hdl.handle.net/10183/22654.

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Esta tese apresenta três ensaios sobre previsão de inflação e análise de dados em tempo real no Brasil. Utilizando uma curva de Phillips, o primeiro ensaio propõe um “modelo evolucionário” para prever inflação no Brasil. O modelo evolucionário consiste em uma combinação de um modelo não-linear (que é formado pela combinação de três redes neurais artificiais – RNAs) e de um modelo linear (que também é a referência para propósitos de comparação). Alguns parâmetros do modelo evolucionário, incluindo os pesos das combinações, evoluem ao longo do tempo segundo ajustes definidos por três algoritmos
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21

Garcia, José Salvado. "Forecasting portuguese Gdp: a comparison of univariate time series models." Master's thesis, 2020. http://hdl.handle.net/10362/104210.

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We perform a forecast evaluation exercise, where a broad set of linear univari-ate models and autoregressive artificial neural networks are compared against a simple linearbenchmark when predicting Portuguese real GDP growth. The forecasting exercise is performedin a pseudo-real-time framework, meaning that the specification and estimation of each modelare delivered for each quarter of the out-of-sample forecast evaluation interval. The efficacy ofthe models is tested for diverse conceptions of the loss functions, different evaluation samples,and estimation procedures. The empirical results p
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22

Philippart, Inês Ribeiro Nunes. "Pseudo real-time forecasting: a model comparison for Portuguese Gdp." Master's thesis, 2021. http://hdl.handle.net/10362/121885.

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GDP is one of the most important economic indicators, yet it presents a significant publishing delay. Many nowcasting models have proven to be successful and have outperformed standard forecasting regressions. This paper compares different nowcasting approaches for estimating quarterly Portuguese GDP, using estimated factors from mixed frequency real-time data. We discuss the out-of-sample forecasting accuracy for each of the models. Furthermore, we investigate the contribution of current-quarter monthly data to the forecasting performance. The results point to an
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23

Hsu, Min-chieh, and 徐敏傑. "Forecasting Taiwan''s GDP,Export,Fixed Investment and Terms of Trade." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/54039104291786967373.

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碩士<br>國立中山大學<br>經濟學研究所<br>104<br>Taiwan is an island surrounded by sea, so the economic growth mostly relies on international trade. Our paper is subject to discuss that the exports impact on the economic growth and follows Tai-Hsin,Huang(2002)” The Causality Export and Economic Growth: The Empirical Study of Taiwan.” to find variables can be explained why exports affect the economic growth. Then, we use Banerjee et al.(2014)”Factor-augmented error correction models”(FECM) to retest the relationship in variables. The FECM resolve the defect that the Vector Auto Regressions (VAR) and the Error
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24

曾子豪. "Analyzing and Forecasting CO2 Emission, Energy Consumption, and Real GDP in the Top New Renewable Energy Countries." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/79gz9p.

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碩士<br>國立交通大學<br>管理科學系所<br>106<br>This study explores the causality among energy (Fossil Fuel and new renewable energy), environment (CO2 emission) and economic (real GDP), which is based on three countries without record of use of nuclear energy and with highest share of renewable energy in the world in 1980 to 2016.As the economic rapidly develop, the use and demand of energy annually grows up. But it also causes the damage and pollution to the environment. For the sustainable development of the environment, each government of countries starts to set new energy policy. In this study, it found
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Lechien, Grégory. "Taking the pulse of the real economy using financial statement analysis: the european perspective." Master's thesis, 2018. http://hdl.handle.net/10362/36557.

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This article shows that an analysis of aggregated changes in profitability and profitability drivers is useful to forecast European economic growth. Furthermore the predictive power contained in profitability ratios is incremental and thus complementary to that contained in stock returns. Although European professional forecasters tend to incorporate equity returns and accounting information in their revisions of output growth expectations, their prediction errors can be anticipated based on aggregate changes in Return on Equity, Net Profit Margin and on stock returns. It implies that ma
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Taylor, Scott O. "Forecasting successional change in dry-mesic forests based on gap capture methods." 1999. http://catalog.hathitrust.org/api/volumes/oclc/44539206.html.

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Thesis (M.S.)--University of Wisconsin--Madison, 1999.<br>Typescript. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 29-33).
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27

Chen, Li-Hui, and 陳麗惠. "Constructing Application Forecasting Models of Interest-sensitive Gap Management in a Commercial Bank." Thesis, 2001. http://ndltd.ncl.edu.tw/handle/59575344740663980472.

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博士<br>銘傳大學<br>管理科學研究所<br>89<br>This paper studied the forecasting problems about interest-sensitive gap management in a commercial bank. The historical data were used to construct the forecasting models. Owing to the Grey forecasting method with the merits of fewer data to fund the forecasting model, it is needless to consider the status of data distribution and the forecasting model is easy to operate. So this paper applied Grey forecasting GM (1,1) model and its generated models, the Grey Markov numerical forecasting model and Comprehension model, to develop a net interest margin change (%)
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