**Table 2.** FLS data—Marginal posterior inclusion probabilities of the covariates

|||_m_|= 7|||_m_=_k/_|2 = 20_._5||
|---|---|---|---|---|---|---|---|---|
||fx|ed_θ_|rand|om_θ_|fx|ed_θ_|rand|om_θ_|
|Regressors|_g_ = 1_/n_|_g_ = 1_/k_<sup>2</sup>|_g_ = 1_/n_|_g_ = 1_/k_<sup>2</sup>|_g_ = 1_/n_|_g_ = 1_/k_<sup>2</sup>|_g_ = 1_/n_|_g_ = 1_/k_<sup>2</sup>|
|log GDP in 1960|1.00|0.91|1.00|0.79|1.00|1.00|1.00|0.84|
|Fraction Confucian|0.99|0.94|1.00|0.93|1.00|1.00|1.00|0.94|
|Life expectancy|0.92|0.74|0.95|0.63|1.00|0.95|0.97|0.68|
|Equipment investment|0.95|0.98|0.93|0.98|0.97|0.94|0.94|0.98|
|Sub-Saharan dummy|0.70|0.59|0.78|0.53|1.00|0.75|0.85|0.55|
|Fraction Muslim|0.62|0.29|0.63|0.23|0.43|0.66|0.61|0.27|
|Rule of law|0.41|0.17|0.56|0.15|0.93|0.52|0.67|0.17|
|Number of years open economy|0.56|0.60|0.46|0.54|0.07|0.50|0.36|0.56|
|Degree of capitalism|0.36|0.09|0.50|0.08|0.56|0.47|0.56|0.09|
|Fraction Protestant|0.38|0.23|0.49|0.24|0.47|0.46|0.51|0.24|
|Fraction GDP in mining|0.36|0.08|0.51|0.07|0.94|0.44|0.63|0.08|
|Non-Equipment investment|0.33|0.07|0.47|0.06|0.71|0.43|0.56|0.07|
|Latin American dummy|0.18|0.09|0.23|0.07|0.75|0.19|0.34|0.08|
|Primary school enrollment, 1960|0.19|0.10|0.21|0.08|0.63|0.18|0.29|0.09|
|Fraction Buddhist|0.14|0.05|0.20|0.07|0.25|0.17|0.23|0.07|
|Black market premium|0.11|0.02|0.22|0.01|0.69|0.16|0.34|0.02|
|Fraction Catholic|0.09|0.03|0.13|0.02|0.12|0.11|0.14|0.03|
|Civil liberties|0.09|0.03|0.13|0.02|0.54|0.10|0.22|0.03|
|Fraction Hindu|0.06|0.07|0.18|0.01|0.97|0.10|0.36|0.01|
|Political rights|0.06|0.01|0.09|0.01|0.29|0.07|0.13|0.02|
|Exchange rate distortions|0.06|0.03|0.06|0.02|0.12|0.06|0.08|0.03|
|Age|0.06|0.02|0.07|0.02|0.25|0.06|0.10|0.02|
|War dummy|0.05|0.02|0.06|0.02|0.14|0.05|0.08|0.02|
|Fraction of Pop. Speaking English|0.04|0.01|0.07|0.01|0.42|0.05|0.15|0.01|
|Size labor force|0.04|0.01|0.11|0.01|0.95|0.05|0.28|0.01|
|Ethnolinguistic fractionalization|0.03|0.01|0.09|0.01|0.87|0.03|0.24|0.01|
|Spanish Colony dummy|0.03|0.01|0.06|0.01|0.59|0.03|0.17|0.01|
|French Colony dummy|0.03|0.01|0.05|0.01|0.54|0.03|0.15|0.01|
|Higher education enrollment|0.02|0.01|0.08|0.01|0.91|0.02|0.24|0.01|
|British colony dummy|0.02|0.00|0.04|0.00|0.47|0.02|0.13|0.00|
|Outward orientation|0.02|0.01|0.04|0.01|0.42|0.02|0.12|0.01|
|Public education share|0.02|0.00|0.03|0.00|0.30|0.02|0.08|0.00|

with _g_ = 1 _/n_ and _m_ = 54 _/_ 2 = 27. Again, however, longer runs do not lead to appreciably different conclusions (see footnote 6).

# _4.3. The Data Set of SDM and DW_

SDM and Doppelhofer and Weeks (2006) use a larger data set, and model annual GDP growth per capita between 1960 and 1996 for _n_ = 88 countries as a function of _k_ = 67 potential drivers.<sup>7</sup> Despite the larger model space (the number of models in _M_ is now 1 _._ 5 _×_ 10<sup>20</sup> ), Table 4 shows that posterior model probabilities are more concentrated than in the previous two cases; in fact, even in those cases where many models are visited, 50% of the posterior mass is still accounted for through a rather small number of models. Also, model sizes tend to be smaller; in fact, the posterior mean model size is less than 3 for three of the four cases with _g_ = 1 _/k_<sup>2</sup> . If we adopt a random 7 The data and the code used in SDM are available at http://www.econ.cam.ac.uk/faculty/doppelhofer/ 14