Grace Alinaitwe

Makerere University Business School 10th ORSEA-15-17October 2014

Growth theories do not clearly specify the explanatory variables to include in the "true" regression.

The debate of whether finance leads or follows economic growth

A few studies have looked at determinants of economic growth using a Bayesian averaging of classical estimates

Negative, positive and none relationships have been found between economic growth and financial intermediaries.

Bayesian Averaging of Classical Estimates

Posterior inclusion probability of a variable shows the importance of a certain variable in explaining the dependent variable

Important variables must have a higher posterior inclusion probability than their prior one.

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BIC weights penalize large models and helps address the problem of colinearity in large models.

Expected model size equals 5, the prior inclusion probability is 5/14 = 0.3571

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The posterior model weights in the above equation are equal to the prior model weights times the Bayesian Information Criterion (BIC) developed by Schwarz (1978) divided by the sum of prior weights times the Bayesian Information Criterion of all possible models.

Similar variables usually explain relatively less variation in the dependent variable and (BIC) implies less weight on such models.

BACE combines the averaging of estimates across models with classical ordinary least-squares (OLS) estimation.

Its advantages over model-averaging

◦ requires the specification of only one prior hyper-parameter the expected model size k

◦ estimates are calculated using only repeated OLS

◦ This method takes into account all the possible models

Variable posterior

prob

Posterior unconditional posterior conditional

Mean st. dev. Mean st. dev

FDI 1 0.0021 0.0002 0.0021 0.0002

Llgdp 0.4108 0.0136 0.0197 0.0332 0.0173

Lcgdp 0.2995 -0.0071 0.0142 -0.0239 0.0166

Popg 0.2792 -0.2317 0.4688 -0.83 0.5391

Fert 0.2608 -0.0016 0.0038 -0.0063 0.0051

INFL 0.1929 0.0001 0.0002 0.0003 0.0002

pcrdbc 0.1873 0.006 0.0172 0.0321 0.0272

Oil 0.1498 -0.0014 0.0048 -0.0091 0.0092

Scho 0.1214 0 0.0001 0.0001 0.0002

Lpop 0.1026 0.0002 0.0016 0.0015 0.0047

cbagdp 0.1004 0.0002 0.0086 0.0021 0.0271

Lpi 0.0872 0.0002 0.0043 0.0025 0.0144

Open 0.0855 -0.0001 0.0029 -0.0007 0.0099

Life 0.0844 0 0.002 -0.0001 0.0069

variable Kbar=3 Kbar=5 Kbar=7 Kbar=9 Kbar=11

prior

inclusion

probalility 0.2143 0.3571 0.5 0.6429 0.7857

FDI 1 1 1 1 1

Llgdp 0.3369 0.4108 0.4733 1 1

Popg 0.2071 0.2792 0.3352 1 1

Fert 0.1704 0.2608 0.3618 1 1

Lcgdp 0.1492 0.2995 0.4936 1 1

Pcrdbc 0.1197 0.1873 0.2656 1 1

INFL 0.1003 0.1929 0.2955 1 1

Oil 0.0743 0.1498 0.215 1 1

Scho 0.0706 0.1214 0.1702 1 1

Lpop 0.0557 0.1026 0.1573 1 1

Cbagdp 0.0509 0.1004 0.1514 1 1

Life 0.0492 0.0844 0.151 1 1

Lpi 0.0454 0.0872 0.1489 1 1

Open 0.0443 0.0855 0.1452 1 1

I thank you for your kind attention