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ATT PROGNOSTISERA DET FINANSIELLA RESULTATET I SVENSKA KOMMUNER EN JÄMFÖRELSE MELLAN ETT ELASTISKT NÄT OCH EN BASELINE

Nilsson, Sofia LU (2020) STAH11 20192
Department of Statistics
Abstract
Machine learning techniques have gained ground in macroeconomic forecasting in recent years. Estimations with the elastic net technique have yielded good results. There is currently not much research on how statistical techniques can be used to estimate the financial result in Swedish municipalities. This study adds to the current body of research by investigating how the elastic net technique can be used to forecast the financial result in Swedish municipalities.

Data is collected from several sources and is used to forecast the financial result in Swedish municipalities. Estimations are carried out using an elastic net and a baseline in the form of OLS and are then compared and discussed. The results show that the estimations using... (More)
Machine learning techniques have gained ground in macroeconomic forecasting in recent years. Estimations with the elastic net technique have yielded good results. There is currently not much research on how statistical techniques can be used to estimate the financial result in Swedish municipalities. This study adds to the current body of research by investigating how the elastic net technique can be used to forecast the financial result in Swedish municipalities.

Data is collected from several sources and is used to forecast the financial result in Swedish municipalities. Estimations are carried out using an elastic net and a baseline in the form of OLS and are then compared and discussed. The results show that the estimations using an elastic net give more accurate forecasts than OLS in Swedish municipalities between 2002 and 2018.

The most accurate forecasting method in this study was the Ridge regression. The study concludes by suggesting how the financial result in Swedish municipalities could be more thoroughly investigated using statistical methods. (Less)
Please use this url to cite or link to this publication:
author
Nilsson, Sofia LU
supervisor
organization
course
STAH11 20192
year
type
M2 - Bachelor Degree
subject
keywords
Elastic net, Ridge regression, Lasso regression, OLS, finances of Swedish municipalities, prediction, forecasting
language
Swedish
id
9033365
date added to LUP
2021-01-07 12:18:23
date last changed
2021-01-15 03:41:04
@misc{9033365,
  abstract     = {{Machine learning techniques have gained ground in macroeconomic forecasting in recent years. Estimations with the elastic net technique have yielded good results. There is currently not much research on how statistical techniques can be used to estimate the financial result in Swedish municipalities. This study adds to the current body of research by investigating how the elastic net technique can be used to forecast the financial result in Swedish municipalities. 

Data is collected from several sources and is used to forecast the financial result in Swedish municipalities. Estimations are carried out using an elastic net and a baseline in the form of OLS and are then compared and discussed. The results show that the estimations using an elastic net give more accurate forecasts than OLS in Swedish municipalities between 2002 and 2018.

The most accurate forecasting method in this study was the Ridge regression. The study concludes by suggesting how the financial result in Swedish municipalities could be more thoroughly investigated using statistical methods.}},
  author       = {{Nilsson, Sofia}},
  language     = {{swe}},
  note         = {{Student Paper}},
  title        = {{ATT PROGNOSTISERA DET FINANSIELLA RESULTATET I SVENSKA KOMMUNER EN JÄMFÖRELSE MELLAN ETT ELASTISKT NÄT OCH EN BASELINE}},
  year         = {{2020}},
}