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Table 4 Determinants of relative price margin

From: Does mobile phone technology reduce agricultural price distortions? Evidence from cocoa and coffee industries

Variables

(1)

(2)

(3)

GDP per capita

0.24624***

0.14381***

0.21119***

(0.03428)

(0.05532)

(0.06067)

Inflation

− 0.00031***

− 0.00029***

− 0.00028***

(0.00002)

(0.00003)

(0.00003)

Public debt

− 0.00039

− 0.00225***

− 0.00223***

(0.00029)

(0.00049)

(0.00050)

Public debt squared

0.00000

0.00000**

0.00000

(0.00000)

(0.00000)

(0.00000)

Polity2

0.02421***

0.03222***

0.03282***

(0.00095)

(0.00159)

(0.00162)

% of Rural population

0.01489***

0.00629*

0.00646*

(0.00205)

(0.00325)

(0.00366)

Land per capita

− 0.40760***

− 0.33199***

− 0.27722***

(0.04146)

(0.06768)

(0.06979)

Mobile phone usage

0.00301***

 

0.00062

(0.00026)

 

(0.00064)

Internet connectivity

 

0.00589***

− 0.00421**

 

(0.00079)

(0.00191)

Mobile*Internet

  

0.00011***

  

(0.00002)

Coffee

0.05421***

0.07431***

0.07383***

(0.00755)

(0.01202)

(0.01217)

South America

0.54560***

0.02254

− 0.22439

(0.13650)

(0.24765)

(0.25574)

Asia

0.09120***

0.07643

0.03850

(0.03437)

(0.05729)

(0.05871)

Constant

− 2.45543***

−0.98560**

− 1.37800**

(0.32398)

(0.50011)

(0.57471)

Total effect of mobile Usage

  

0.0012*

  

(0.0006)

Observations

379

329

329

R-squared

0.31399

0.31701

0.32532

Year FE

Yes

Yes

Yes

Country FE

Yes

Yes

Yes

Adjusted R-squared

0.221

0.208

0.212

Long run SE

0.0461

0.0674

0.0682

Bandwidth (neweywest)

305.5

123

124.3

  1. Standard errors in parentheses
  2. ***p < 0.01; **p < 0.05; *p < 0.1