Beyond Political Connections : A Measurement Model Approach to Estimating Firm-level Political Influence in 41 Economies
This paper considers the political influence of private firms. While such influence is frequently discussed, there is limited analysis of how firms combine political interactions, and under what conditions, to gain influence. The exception is the l...
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Washington, DC : World Bank
2022
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| Online Access: | http://documents.worldbank.org/curated/en/099855207052233298/IDU0158ecaac01be104fd80a04a03c9cf1992a74 http://hdl.handle.net/10986/37646 |
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okr-10986-376462022-07-07T05:10:44Z Beyond Political Connections : A Measurement Model Approach to Estimating Firm-level Political Influence in 41 Economies Francis, David C. Kubinec, Robert POLITICAL INFLUENCE POLITICAL CONNECTIONS PRIVATE FIRMS BAYESIAN LATENT VARIABLES This paper considers the political influence of private firms. While such influence is frequently discussed, there is limited analysis of how firms combine political interactions, and under what conditions, to gain influence. The exception is the large literature on firms with political connections, with findings generally showing large gains to firms with those direct relationships. This paper extends the discussion of influence beyond political connections alone and uses a rich firm-level data set from 41 economies, which includes information on several interactions with political actors. Using a Bayesian item response theory (IRT) measurement model, an index of Political Influence is estimated, with the prior assumption that political connections yield more influence. Membership in a business association is found to enhance influence, while such influence is offset by bribes, state ownership, firm size, and a reliance on collective lobbying. Political Influence is found to be broadly higher in economies with poorer governance but more dispersed in those with better governance. Within economies, higher influence is associated with a higher likelihood of reporting a small number of competitors, higher sales, and lower labor inputs relative to sales. These findings are robust across several models that incorporate high-dimensional fixed effects, incorporating measurement error in the index, and varying these relationships over several governance measures. 2022-07-06T17:22:40Z 2022-07-06T17:22:40Z 2022-07 Working Paper http://documents.worldbank.org/curated/en/099855207052233298/IDU0158ecaac01be104fd80a04a03c9cf1992a74 http://hdl.handle.net/10986/37646 English en_US Policy Research Working Paper;10119 CC BY 3.0 IGO http://creativecommons.org/licenses/by/3.0/igo World Bank Washington, DC : World Bank Publications & Research Publications & Research :: Policy Research Working Paper World |
| repository_type |
Digital Repository |
| institution_category |
Foreign Institution |
| institution |
Digital Repositories |
| building |
World Bank Open Knowledge Repository |
| collection |
World Bank |
| language |
English en_US |
| topic |
POLITICAL INFLUENCE POLITICAL CONNECTIONS PRIVATE FIRMS BAYESIAN LATENT VARIABLES |
| spellingShingle |
POLITICAL INFLUENCE POLITICAL CONNECTIONS PRIVATE FIRMS BAYESIAN LATENT VARIABLES Francis, David C. Kubinec, Robert Beyond Political Connections : A Measurement Model Approach to Estimating Firm-level Political Influence in 41 Economies |
| geographic_facet |
World |
| relation |
Policy Research Working Paper;10119 |
| description |
This paper considers the political
influence of private firms. While such influence is
frequently discussed, there is limited analysis of how firms
combine political interactions, and under what conditions,
to gain influence. The exception is the large literature on
firms with political connections, with findings generally
showing large gains to firms with those direct
relationships. This paper extends the discussion of
influence beyond political connections alone and uses a rich
firm-level data set from 41 economies, which includes
information on several interactions with political actors.
Using a Bayesian item response theory (IRT) measurement
model, an index of Political Influence is estimated, with
the prior assumption that political connections yield more
influence. Membership in a business association is found to
enhance influence, while such influence is offset by bribes,
state ownership, firm size, and a reliance on collective
lobbying. Political Influence is found to be broadly higher
in economies with poorer governance but more dispersed in
those with better governance. Within economies, higher
influence is associated with a higher likelihood of
reporting a small number of competitors, higher sales, and
lower labor inputs relative to sales. These findings are
robust across several models that incorporate
high-dimensional fixed effects, incorporating measurement
error in the index, and varying these relationships over
several governance measures. |
| format |
Working Paper |
| author |
Francis, David C. Kubinec, Robert |
| author_facet |
Francis, David C. Kubinec, Robert |
| author_sort |
Francis, David C. |
| title |
Beyond Political Connections : A Measurement Model Approach to Estimating Firm-level Political Influence in 41 Economies |
| title_short |
Beyond Political Connections : A Measurement Model Approach to Estimating Firm-level Political Influence in 41 Economies |
| title_full |
Beyond Political Connections : A Measurement Model Approach to Estimating Firm-level Political Influence in 41 Economies |
| title_fullStr |
Beyond Political Connections : A Measurement Model Approach to Estimating Firm-level Political Influence in 41 Economies |
| title_full_unstemmed |
Beyond Political Connections : A Measurement Model Approach to Estimating Firm-level Political Influence in 41 Economies |
| title_sort |
beyond political connections : a measurement model approach to estimating firm-level political influence in 41 economies |
| publisher |
Washington, DC : World Bank |
| publishDate |
2022 |
| url |
http://documents.worldbank.org/curated/en/099855207052233298/IDU0158ecaac01be104fd80a04a03c9cf1992a74 http://hdl.handle.net/10986/37646 |
| _version_ |
1764487599357952000 |