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st: xtabond & xtabond2: impact of insurance on GDP growth


From   Yen Nguyen <Yen.Nguyen@buseco.monash.edu.au>
To   statalist@hsphsun2.harvard.edu
Subject   st: xtabond & xtabond2: impact of insurance on GDP growth
Date   Tue, 07 Oct 2008 20:54:35 +1100

Hi Stata users

I'm running two panel data looking at impact of insurance (as well as banking, stock market) on economic growth (GDP growth - gdpg). This is similar to the work of Levine, Beck & Loayza (2000) "Finance intermediation and growth: causality and causes", and Arena (2006) "Does insurance market activity promote economic growth?".

Annual panel, T=26, N=60 --> xtabond difference GMM

Five-year average panel: T=5, N=59 --> xtabond2 system GMM

Both are unbalanced panel (due to lack of data for all the years).


I use GDP growth (gdpg calculated by difference in log real GDP per capita) as dependent variable.

Expected signs for independent variables (insurance premium/GDP (penetration), banking, stock market turnover) are positive.

However, always get negative sign for all the independent variables in xtabond (annual) and insignificant results in xtabond2 (five year average). Sargan test and A-B second order correlation test are okie (accepted)for both.

. xtabond gdpg pene_t bank stock lgdpi 
> govt linf open tot, lags(1) maxldep(25)
> twostep artests(2);

Arellano-Bond dynamic panel-data estimation     Number of obs      =       902
Group variable (i): country                     Number of groups   =        64

                                                Wald chi2(9)       =   4598.67

Time variable (t): year                         Obs per group: min =         1
                                                               avg =  14.09375
                                                               max =        25

Two-step results
------------------------------------------------------------------------------
      D.gdpg |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
        gdpg |
         LD. |   .0951484   .0108329     8.78   0.000     .0739163    .1163804
      pene_t |
         D1. |   -.359937   .0477571    -7.54   0.000    -.4535392   -.2663349
        bank |
         D1. |  -.0373582   .0049504    -7.55   0.000    -.0470608   -.0276556
       stock |
         D1. |    .005358   .0004958    10.81   0.000     .0043863    .0063297
       lgdpi |
         D1. |   .0735472   .0071024    10.36   0.000     .0596267    .0874676
        govt |
         D1. |  -.0795676   .0095947    -8.29   0.000    -.0983728   -.0607624
        linf |
         D1. |  -.0137611   .0022353    -6.16   0.000    -.0181422     -.00938
        open |
         D1. |   .0097536   .0041788     2.33   0.020     .0015633    .0179439
         tot |
         D1. |   .0149388   .0026216     5.70   0.000     .0098005    .0200771
       _cons |  -.0007371   .0001217    -6.05   0.000    -.0009757   -.0004984
------------------------------------------------------------------------------


xtabond2:
xtabond2 pgdpg L.pgdpg L(0/1).(ppene_t pbank 
>         plgdpi popen pgovt plinf ptot) period2-period5
>         , gmm(l.pgdpg ppene_t pbank)
>         iv(period2-period5) robust twostep artests(2);


Dynamic panel-data estimation, two-step system GMM
------------------------------------------------------------------------------
Group variable: country                         Number of obs      =       183
Time variable : year                            Number of groups   =        57
Number of instruments = 39                      Obs per group: min =         1
Wald chi2(18) =     77.62                                      avg =      3.21
Prob > chi2   =     0.000                                      max =         4
------------------------------------------------------------------------------
             |              Corrected
       pgdpg |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       pgdpg |
         L1. |  -.9711892   .6954424    -1.40   0.163    -2.334231    .3918528
     ppene_t |
         --. |   .0131906   .1759554     0.07   0.940    -.3316756    .3580568
         L1. |   .0052757   .1954426     0.03   0.978    -.3777847     .388336
       pbank |
         --. |   .0021213   .0054946     0.39   0.699     -.008648    .0128906
         L1. |  -.0058175   .0093167    -0.62   0.532    -.0240779    .0124429
      plgdpi |
         --. |   .0727495    .054013     1.35   0.178    -.0331141    .1786131
         L1. |  -.0751615    .056488    -1.33   0.183    -.1858759    .0355529
       popen |
         --. |   .0178883   .0125482     1.43   0.154    -.0067058    .0424824
         L1. |  -.0165761   .0136101    -1.22   0.223    -.0432514    .0100992
       pgovt |
         --. |   -.182051   .1468107    -1.24   0.215    -.4697947    .1056927
         L1. |   .1615535   .1007263     1.60   0.109    -.0358663    .3589734
       plinf |
         --. |  -.0639689   .0229701    -2.78   0.005    -.1089895   -.0189483
         L1. |  -.0102448   .0122008    -0.84   0.401    -.0341579    .0136684
        ptot |
         --. |   .2249072   .2673885     0.84   0.400    -.2991648    .7489791
         L1. |  -.0815871   .1382154    -0.59   0.555    -.3524844    .1893101
     period2 |    .000801   .0038174     0.21   0.834     -.006681     .008283
     period3 |   .0033025   .0034863     0.95   0.343    -.0035304    .0101355
     period4 |  -.0024695   .0020707    -1.19   0.233    -.0065281    .0015891
       _cons |   .0399558   .0255705     1.56   0.118    -.0101614    .0900731
------------------------------------------------------------------------------

I wonder whether anyone has experienced this before? I have tried to separate the countries into group of developed & developing countries, but still same result. Also I wonder whether my xtabond2 is structured correctly.

Or is it because my N is too small?

Thanks a lot,
Yen Nguyen
Monash University
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