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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