Firm Level Analysis of Services Trade Restrictions in the Life Insurance Industry

Tamar Khachaturian and Sarah Oliver

 

Accompanying Equations (HTML Version)

 

Estimation Framework

The focus of this analysis is the effect of life insurance trade restrictions on market participation, as measured by the number of firms in each country, and on profit margins. The number of firms and average profit margins are calculated using the firm-level data described in section 4 and in the appendix. The main policy variable is the World Bank’s STRI for mode 3 life insurance. The index reflects licensing restrictions, foreign equity limits and other policies affecting the commercial establishment and operation of foreign life insurance firms.

First, a simple cross-sectional regression estimates the impact of the STRI level on the number of firms in each country. Equation (1) is the basic form of the model:

( 1 ) lnNumber of firm s i 2011  =  β 1 + β 2 STR I i 2008 + ε i 2011   MathType@MTEF@5@5@+= feaagKart1ev2aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVCI8FfYJH8YrFfeuY=Hhbbf9v8qqaqFr0xc9pk0xbb a9q8WqFfeaY=biLkVcLq=JHqpepeea0=as0Fb9pgeaYRXxe9vr0=vr 0=vqpWqaaeaabiGaciaacaqabeaadaqaaqaaaOqaaabaaaaaaaaape WaaeWaa8aabaWdbiaaigdaaiaawIcacaGLPaaaieWacaWFGcGaa8hB aiaa=5gacaWFobGaa8xDaiaa=1gacaWFIbGaa8xzaiaa=jhacaWFGc Gaa83Baiaa=zgacaWFGcGaa8Nzaiaa=LgacaWFYbGaa8xBaiaa=nha paWaaSbaaSqaa8qacaWFPbGaa8hOaiaaikdacaaIWaGaaGymaiaaig dacaWFGcaapaqabaGcpeGaeyypa0Jaa8hOaiaa=j7apaWaaSbaaSqa a8qacaaIXaaapaqabaGcpeGaey4kaSIaa8NSd8aadaWgaaWcbaWdbi aaikdaa8aabeaak8qacaWFtbGaa8hvaiaa=jfacaWFjbWdamaaBaaa leaapeGaa8xAaiaa=bkacaaIYaGaaGimaiaaicdacaaI4aaapaqaba GcpeGaey4kaSIaa8xTd8aadaWgaaWcbaWdbiaa=LgacaWFGcGaaGOm aiaaicdacaaIXaGaaGymaaWdaeqaaOWaaSbaaSqaa8qacaWFGcaapa qabaaaaa@699F@  

The dependent variable is the number of firms in country i in 2011. Additional controls are added in model 2: level of development, proxied by whether the country is categorized as a high-income country, and the log of population.[1] While the STRI is expected to have a negative impact on the number of firms, level of development and country size are expected to have positive impacts:

( 2 ) lnNumber of firm s i 2011  =  β 1 + β 2 STR I i 2008 + β 3 High Incom e i2011 +   β 4 lnPopulatio n i 2011  + ε i 2011   MathType@MTEF@5@5@+= feaagKart1ev2aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVCI8FfYJH8YrFfeuY=Hhbbf9v8qqaqFr0xc9pk0xbb a9q8WqFfeaY=biLkVcLq=JHqpepeea0=as0Fb9pgeaYRXxe9vr0=vr 0=vqpWqaaeaabiGaciaacaqabeaadaqaaqaaaOqaaabaaaaaaaaape WaaeWaa8aabaWdbiaaikdaaiaawIcacaGLPaaaieWacaWFGcGaa8hB aiaa=5gacaWFobGaa8xDaiaa=1gacaWFIbGaa8xzaiaa=jhacaWFGc Gaa83Baiaa=zgacaWFGcGaa8Nzaiaa=LgacaWFYbGaa8xBaiaa=nha paWaaSbaaSqaa8qacaWFPbGaa8hOaiaaikdacaaIWaGaaGymaiaaig dacaWFGcaapaqabaGcpeGaeyypa0Jaa8hOaiaa=j7apaWaaSbaaSqa a8qacaaIXaaapaqabaGcpeGaey4kaSIaa8NSd8aadaWgaaWcbaWdbi aaikdaa8aabeaak8qacaWFtbGaa8hvaiaa=jfacaWFjbWdamaaBaaa leaapeGaa8xAaiaa=bkacaaIYaGaaGimaiaaicdacaaI4aaapaqaba GcpeGaey4kaSIaa8NSd8aadaWgaaWcbaWdbiaaiodaa8aabeaak8qa caWFibGaa8xAaiaa=DgacaWFObGaa8hOaiaa=LeacaWFUbGaa83yai aa=9gacaWFTbGaa8xza8aadaWgaaWcbaWdbiaa=LgacaaIYaGaaGim aiaaigdacaaIXaaapaqabaGcpeGaey4kaSYdamaaBaaaleaapeGaa8 hOaaWdaeqaaOWdbiaa=j7apaWaaSbaaSqaa8qacaaI0aaapaqabaGc peGaa8hBaiaa=5gacaWFqbGaa83Baiaa=bhacaWF1bGaa8hBaiaa=f gacaWF0bGaa8xAaiaa=9gacaWFUbWdamaaBaaaleaapeGaa8xAaiaa =bkacaaIYaGaaGimaiaaigdacaaIXaaapaqabaGcpeGaa8hOaiabgU caRiaa=v7apaWaaSbaaSqaa8qacaWFPbGaa8hOaiaaikdacaaIWaGa aGymaiaaigdaa8aabeaakmaaBaaaleaapeGaa8hOaaWdaeqaaaaa@91B5@

The above models are estimated using both a linear regression and a non-linear Poisson model where the dependent variable is in levels rather than logs. In addition to the analysis of the total number of firms in a country market, these models are estimated separately for SMEs and large firms as well as for the ratio of SMEs to all firms in the country as the dependent variables.

Second, models estimate the impact of the STRI level on the average profitability of firms in a given market, measured as profit before taxes over net premiums written:[2]

( 3 ) Average Profit Margi n i 2011  =  γ 1 + γ 2 STR I i 2008 + ω i 2011   MathType@MTEF@5@5@+= feaagKart1ev2aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVCI8FfYJH8YrFfeuY=Hhbbf9v8qqaqFr0xc9pk0xbb a9q8WqFfeaY=biLkVcLq=JHqpepeea0=as0Fb9pgeaYRXxe9vr0=vr 0=vqpWqaaeaabiGaciaacaqabeaadaqaaqaaaOqaaabaaaaaaaaape WaaeWaa8aabaWdbiaaiodaaiaawIcacaGLPaaaieWacaWFGcGaa8xq aiaa=zhacaWFLbGaa8NCaiaa=fgacaWFNbGaa8xzaiaa=bkacaWFqb Gaa8NCaiaa=9gacaWFMbGaa8xAaiaa=rhacaWFGcGaa8xtaiaa=fga caWFYbGaa83zaiaa=LgacaWFUbWdamaaBaaaleaapeGaa8xAaiaa=b kacaaIYaGaaGimaiaaigdacaaIXaGaa8hOaaWdaeqaaOWdbiabg2da 9iaa=bkacaWFZoWdamaaBaaaleaapeGaaGymaaWdaeqaaOWdbiabgU caRiaa=n7apaWaaSbaaSqaa8qacaaIYaaapaqabaGcpeGaa83uaiaa =rfacaWFsbGaa8xsa8aadaWgaaWcbaWdbiaa=LgacaWFGcGaaGOmai aaicdacaaIWaGaaGioaaWdaeqaaOWdbiabgUcaRiaa=L8apaWaaSba aSqaa8qacaWFPbGaa8hOaiaaikdacaaIWaGaaGymaiaaigdaa8aabe aakmaaBaaaleaapeGaa8hOaaWdaeqaaaaa@6D0F@

and

                ( 4 ) Average Profit Margi n i 2011 =  γ 1 + γ 2 STR I i 2008 + γ 3 High Incom e i2011 +   γ 4 lnPopulatio n i 2011  + ω i 2011   MathType@MTEF@5@5@+= feaagKart1ev2aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVCI8FfYJH8YrFfeuY=Hhbbf9v8qqaqFr0xc9pk0xbb a9q8WqFfeaY=biLkVcLq=JHqpepeea0=as0Fb9pgeaYRXxe9vr0=vr 0=vqpWqaaeaabiGaciaacaqabeaadaqaaqaaaOqaaabaaaaaaaaape WaaeWaa8aabaWdbiaaisdaaiaawIcacaGLPaaaieWacaWFGcGaa8xq aiaa=zhacaWFLbGaa8NCaiaa=fgacaWFNbGaa8xzaiaa=bkacaWFqb Gaa8NCaiaa=9gacaWFMbGaa8xAaiaa=rhacaWFGcGaa8xtaiaa=fga caWFYbGaa83zaiaa=LgacaWFUbWdamaaBaaaleaapeGaa8xAaiaa=b kacaaIYaGaaGimaiaaigdacaaIXaaapaqabaGcpeGaeyypa0Jaa8hO aiaa=n7apaWaaSbaaSqaa8qacaaIXaaapaqabaGcpeGaey4kaSIaa8 3Sd8aadaWgaaWcbaWdbiaaikdaa8aabeaak8qacaWFtbGaa8hvaiaa =jfacaWFjbWdamaaBaaaleaapeGaa8xAaiaa=bkacaaIYaGaaGimai aaicdacaaI4aaapaqabaGcpeGaey4kaSIaa83Sd8aadaWgaaWcbaWd biaaiodaa8aabeaak8qacaWFibGaa8xAaiaa=DgacaWFObGaa8hOai aa=LeacaWFUbGaa83yaiaa=9gacaWFTbGaa8xza8aadaWgaaWcbaWd biaa=LgacaaIYaGaaGimaiaaigdacaaIXaaapaqabaGcpeGaey4kaS YdamaaBaaaleaapeGaa8hOaaWdaeqaaOWdbiaa=n7apaWaaSbaaSqa a8qacaaI0aaapaqabaGcpeGaa8hBaiaa=5gacaWFqbGaa83Baiaa=b hacaWF1bGaa8hBaiaa=fgacaWF0bGaa8xAaiaa=9gacaWFUbWdamaa BaaaleaapeGaa8xAaiaa=bkacaaIYaGaaGimaiaaigdacaaIXaaapa qabaGcpeGaa8hOaiabgUcaRiaa=L8apaWaaSbaaSqaa8qacaWFPbGa a8hOaiaaikdacaaIWaGaaGymaiaaigdaa8aabeaakmaaBaaaleaape Gaa8hOaaWdaeqaaaaa@9406@

 


[1] Population data are from the World Bank, World Development Indicators (accessed June 30, 2015) https://data.worldbank.org/data-catalog/world-development-indicators.The dummy variable  for level of development is from the World Bank’s categorization of income categories and equals 1 if the country is included in the high-income category; data are from the historical classification by income, available at World Bank, World Bank Country and Lending Groups (accessed September 1, 2016) https://datahelpdesk.worldbank.org/knowledgebase/articles/906519.

[2] This approach follows the unconditional average approach in Khachaturian (2015), with a simpler framework that excludes industry-specific and other controls.