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Does accounting details play an allocative role in predicting macroeconomic indicators? Evidence of Bayesian and classical econometrics in Iran
Purpose The purpose of this study is to analyze the predictability of firm level data for determining macroeconomic indicators such as unemployment. Design/methodology/approach This study uses quarterly GDP and unemployment data manually collected from the Statistical Center of Iran (SCI). Accountin...
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Published in: | International journal of organizational analysis (2005) 2021-01, Vol.29 (1), p.194-219 |
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container_title | International journal of organizational analysis (2005) |
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creator | Salehi, Mahdi Daemi Gah, Ali Akbari, Farzana Naghshbandi, Nader |
description | Purpose
The purpose of this study is to analyze the predictability of firm level data for determining macroeconomic indicators such as unemployment.
Design/methodology/approach
This study uses quarterly GDP and unemployment data manually collected from the Statistical Center of Iran (SCI). Accounting numbers are also collected from the Tehran Stock Exchange library for the 2004-2015 period. Dispersion of earnings growth provides related data about labour reallocation, unemployment change and finally aggregate output. To summarize, this study attempts to examine the effect of these variables using classical and Bayesian approaches.
Findings
At a firm level, our results suggest that sectoral shift in previous years is likely to increase labour reallocation in subsequent years. At the macro level, the results reveal that dispersion of earnings growth and labour reallocation has a negative and positive impact on unemployment changes, respectively. However, the study suggests no significant relationship between stock return and unemployment changes. Consequently, we determine that the real estimates of macroeconomic indicators have predictive power because nominal estimates are not statistically associated with firm-level details. Finally, the results obtained from classical and Bayesian approaches suggest similar findings, thus confirming the robustness of our conclusions. Note that, based on Bayesian approach, the nominal reallocation has predictive power in unemployment rate.
Originality/value
The study is the first conducted in a developing country and the results provide important insight into current line of accounting literature. |
doi_str_mv | 10.1108/IJOA-10-2019-1902 |
format | article |
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The purpose of this study is to analyze the predictability of firm level data for determining macroeconomic indicators such as unemployment.
Design/methodology/approach
This study uses quarterly GDP and unemployment data manually collected from the Statistical Center of Iran (SCI). Accounting numbers are also collected from the Tehran Stock Exchange library for the 2004-2015 period. Dispersion of earnings growth provides related data about labour reallocation, unemployment change and finally aggregate output. To summarize, this study attempts to examine the effect of these variables using classical and Bayesian approaches.
Findings
At a firm level, our results suggest that sectoral shift in previous years is likely to increase labour reallocation in subsequent years. At the macro level, the results reveal that dispersion of earnings growth and labour reallocation has a negative and positive impact on unemployment changes, respectively. However, the study suggests no significant relationship between stock return and unemployment changes. Consequently, we determine that the real estimates of macroeconomic indicators have predictive power because nominal estimates are not statistically associated with firm-level details. Finally, the results obtained from classical and Bayesian approaches suggest similar findings, thus confirming the robustness of our conclusions. Note that, based on Bayesian approach, the nominal reallocation has predictive power in unemployment rate.
Originality/value
The study is the first conducted in a developing country and the results provide important insight into current line of accounting literature.</description><identifier>ISSN: 1934-8835</identifier><identifier>EISSN: 1758-8561</identifier><identifier>DOI: 10.1108/IJOA-10-2019-1902</identifier><language>eng</language><publisher>Bingley: Emerald Publishing Limited</publisher><subject>Accounting ; Bayesian analysis ; Econometrics ; Economic conditions ; Economic growth ; Economists ; Employees ; Employment ; Financial statements ; Foreign exchange markets ; GDP ; Gross Domestic Product ; Macroeconomics ; Rates of return ; Securities markets ; Stock exchanges ; Unemployment ; Wages & salaries ; Workers</subject><ispartof>International journal of organizational analysis (2005), 2021-01, Vol.29 (1), p.194-219</ispartof><rights>Emerald Publishing Limited</rights><rights>Emerald Publishing Limited 2020</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c314t-85aa6094145c47848ad869c786377e2b7b5bd952c81376f66470ae006bd108f13</citedby><cites>FETCH-LOGICAL-c314t-85aa6094145c47848ad869c786377e2b7b5bd952c81376f66470ae006bd108f13</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2534125907/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$H</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2534125907?pq-origsite=primo$$EHTML$$P50$$Gproquest$$H</linktohtml><link.rule.ids>314,780,784,11688,27924,27925,36060,44363,74767</link.rule.ids></links><search><creatorcontrib>Salehi, Mahdi</creatorcontrib><creatorcontrib>Daemi Gah, Ali</creatorcontrib><creatorcontrib>Akbari, Farzana</creatorcontrib><creatorcontrib>Naghshbandi, Nader</creatorcontrib><title>Does accounting details play an allocative role in predicting macroeconomic indicators? Evidence of Bayesian and classical econometrics in Iran</title><title>International journal of organizational analysis (2005)</title><description>Purpose
The purpose of this study is to analyze the predictability of firm level data for determining macroeconomic indicators such as unemployment.
Design/methodology/approach
This study uses quarterly GDP and unemployment data manually collected from the Statistical Center of Iran (SCI). Accounting numbers are also collected from the Tehran Stock Exchange library for the 2004-2015 period. Dispersion of earnings growth provides related data about labour reallocation, unemployment change and finally aggregate output. To summarize, this study attempts to examine the effect of these variables using classical and Bayesian approaches.
Findings
At a firm level, our results suggest that sectoral shift in previous years is likely to increase labour reallocation in subsequent years. At the macro level, the results reveal that dispersion of earnings growth and labour reallocation has a negative and positive impact on unemployment changes, respectively. However, the study suggests no significant relationship between stock return and unemployment changes. Consequently, we determine that the real estimates of macroeconomic indicators have predictive power because nominal estimates are not statistically associated with firm-level details. Finally, the results obtained from classical and Bayesian approaches suggest similar findings, thus confirming the robustness of our conclusions. Note that, based on Bayesian approach, the nominal reallocation has predictive power in unemployment rate.
Originality/value
The study is the first conducted in a developing country and the results provide important insight into current line of accounting literature.</description><subject>Accounting</subject><subject>Bayesian analysis</subject><subject>Econometrics</subject><subject>Economic conditions</subject><subject>Economic growth</subject><subject>Economists</subject><subject>Employees</subject><subject>Employment</subject><subject>Financial statements</subject><subject>Foreign exchange markets</subject><subject>GDP</subject><subject>Gross Domestic Product</subject><subject>Macroeconomics</subject><subject>Rates of return</subject><subject>Securities markets</subject><subject>Stock exchanges</subject><subject>Unemployment</subject><subject>Wages & salaries</subject><subject>Workers</subject><issn>1934-8835</issn><issn>1758-8561</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>M0C</sourceid><recordid>eNptkUFOwzAQRSMEEqVwAHaWWAfsJI6dFSqlQFGlbmAdTZ0JcuXawU4r9RRcGYewQWLlsf3_H82bJLlm9JYxKu-Wr-tZymiaUValrKLZSTJhgstU8pKdxrrKi1TKnJ8nFyFsKeVCSDFJvh4dBgJKub3ttf0gDfagTSCdgSMBS8AYp6DXByTeGSTaks5jo9WPegfKO1TOup1W8S--Q-98uCeLg27QKiSuJQ9wxKCHMNsQZSCEKDNk9GHvtQpD7tKDvUzOWjABr37PafL-tHibv6Sr9fNyPlulKmdFH6cCKGlVsIKrQshCQiPLSglZ5kJgthEbvmkqninJclG2ZVkICkhpuWkirZbl0-RmzO28-9xj6Out23sbW9YZzwuW8YqKqGKjKk4Zgse27rzegT_WjNYD93rgPlwG7vXAPXro6MEdejDNv5Y_q8q_Aa3Ehbk</recordid><startdate>20210125</startdate><enddate>20210125</enddate><creator>Salehi, Mahdi</creator><creator>Daemi Gah, Ali</creator><creator>Akbari, Farzana</creator><creator>Naghshbandi, Nader</creator><general>Emerald Publishing Limited</general><general>Emerald Group Publishing Limited</general><scope>AAYXX</scope><scope>CITATION</scope><scope>0U~</scope><scope>1-H</scope><scope>7WY</scope><scope>7WZ</scope><scope>7XB</scope><scope>8AO</scope><scope>8FI</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>F~G</scope><scope>GNUQQ</scope><scope>K6~</scope><scope>K8~</scope><scope>L.-</scope><scope>L.0</scope><scope>M0C</scope><scope>M0T</scope><scope>M2M</scope><scope>PQBIZ</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PSYQQ</scope><scope>Q9U</scope><scope>S0X</scope></search><sort><creationdate>20210125</creationdate><title>Does accounting details play an allocative role in predicting macroeconomic indicators? Evidence of Bayesian and classical econometrics in Iran</title><author>Salehi, Mahdi ; Daemi Gah, Ali ; Akbari, Farzana ; Naghshbandi, Nader</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c314t-85aa6094145c47848ad869c786377e2b7b5bd952c81376f66470ae006bd108f13</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Accounting</topic><topic>Bayesian analysis</topic><topic>Econometrics</topic><topic>Economic conditions</topic><topic>Economic growth</topic><topic>Economists</topic><topic>Employees</topic><topic>Employment</topic><topic>Financial statements</topic><topic>Foreign exchange markets</topic><topic>GDP</topic><topic>Gross Domestic Product</topic><topic>Macroeconomics</topic><topic>Rates of return</topic><topic>Securities markets</topic><topic>Stock exchanges</topic><topic>Unemployment</topic><topic>Wages & salaries</topic><topic>Workers</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Salehi, Mahdi</creatorcontrib><creatorcontrib>Daemi Gah, Ali</creatorcontrib><creatorcontrib>Akbari, Farzana</creatorcontrib><creatorcontrib>Naghshbandi, Nader</creatorcontrib><collection>CrossRef</collection><collection>Global News & ABI/Inform Professional</collection><collection>Trade PRO</collection><collection>ABI/INFORM Collection</collection><collection>ABI/INFORM Global (PDF only)</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ProQuest Pharma Collection</collection><collection>Hospital Premium Collection</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Business Premium Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>Health Research Premium Collection</collection><collection>ABI/INFORM Global (Corporate)</collection><collection>ProQuest Central Student</collection><collection>ProQuest Business Collection</collection><collection>DELNET Management Collection</collection><collection>ABI/INFORM Professional Advanced</collection><collection>ABI/INFORM Professional Standard</collection><collection>ABI/INFORM Collection</collection><collection>Health Management Database (Proquest)</collection><collection>Psychology Database (ProQuest)</collection><collection>One Business (ProQuest)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest One Psychology</collection><collection>ProQuest Central Basic</collection><collection>SIRS Editorial</collection><jtitle>International journal of organizational analysis (2005)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Salehi, Mahdi</au><au>Daemi Gah, Ali</au><au>Akbari, Farzana</au><au>Naghshbandi, Nader</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Does accounting details play an allocative role in predicting macroeconomic indicators? Evidence of Bayesian and classical econometrics in Iran</atitle><jtitle>International journal of organizational analysis (2005)</jtitle><date>2021-01-25</date><risdate>2021</risdate><volume>29</volume><issue>1</issue><spage>194</spage><epage>219</epage><pages>194-219</pages><issn>1934-8835</issn><eissn>1758-8561</eissn><abstract>Purpose
The purpose of this study is to analyze the predictability of firm level data for determining macroeconomic indicators such as unemployment.
Design/methodology/approach
This study uses quarterly GDP and unemployment data manually collected from the Statistical Center of Iran (SCI). Accounting numbers are also collected from the Tehran Stock Exchange library for the 2004-2015 period. Dispersion of earnings growth provides related data about labour reallocation, unemployment change and finally aggregate output. To summarize, this study attempts to examine the effect of these variables using classical and Bayesian approaches.
Findings
At a firm level, our results suggest that sectoral shift in previous years is likely to increase labour reallocation in subsequent years. At the macro level, the results reveal that dispersion of earnings growth and labour reallocation has a negative and positive impact on unemployment changes, respectively. However, the study suggests no significant relationship between stock return and unemployment changes. Consequently, we determine that the real estimates of macroeconomic indicators have predictive power because nominal estimates are not statistically associated with firm-level details. Finally, the results obtained from classical and Bayesian approaches suggest similar findings, thus confirming the robustness of our conclusions. Note that, based on Bayesian approach, the nominal reallocation has predictive power in unemployment rate.
Originality/value
The study is the first conducted in a developing country and the results provide important insight into current line of accounting literature.</abstract><cop>Bingley</cop><pub>Emerald Publishing Limited</pub><doi>10.1108/IJOA-10-2019-1902</doi><tpages>26</tpages></addata></record> |
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source | ABI/INFORM Collection; Emerald:Jisc Collections:Emerald Subject Collections HE and FE 2024-2026:Emerald Premier (reading list) |
subjects | Accounting Bayesian analysis Econometrics Economic conditions Economic growth Economists Employees Employment Financial statements Foreign exchange markets GDP Gross Domestic Product Macroeconomics Rates of return Securities markets Stock exchanges Unemployment Wages & salaries Workers |
title | Does accounting details play an allocative role in predicting macroeconomic indicators? Evidence of Bayesian and classical econometrics in Iran |
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