Table 4 Regression models for public...

Table 4

Regression models for public value creation and corruption

	All countries pooled		Development		Technology
	Linear	Non-linear	Low/High	Continuous	Low/High	Continuous
Corruption	-0.891***	-0.320**	-0.714***	-1.082***	-0.742***	-1.170***
Corruption squared		-0.00556***
Developmentally behind			12.14**
- Interaction with corruption			-0.273**
Development level				-0.114
- Interaction with corruption				0.00472***
Technologically behind					10.44*
- Interaction with corruption					-0.232**
Technological level						-0.194*
- Interaction with corruption						0.00557***
Constant	108.1***	96.82***	102.3***	112.0***	103.0***	118.8***
Sample size	187	187	187	187	187	187
R-squared	0.816	0.838	0.827	0.852	0.825	0.849

	All countries pooled		Development		Technology
	Linear	Non-linear	Low/High	Continuous	Low/High	Continuous
Corruption	-0.891***	-0.320**	-0.714***	-1.082***	-0.742***	-1.170***
Corruption squared		-0.00556***
Developmentally behind			12.14**
- Interaction with corruption			-0.273**
Development level				-0.114
- Interaction with corruption				0.00472***
Technologically behind					10.44*
- Interaction with corruption					-0.232**
Technological level						-0.194*
- Interaction with corruption						0.00557***
Constant	108.1***	96.82***	102.3***	112.0***	103.0***	118.8***
Sample size	187	187	187	187	187	187
R-squared	0.816	0.838	0.827	0.852	0.825	0.849

* p<0.05, ** p<0.01, *** p<0.001.

Note: Developmentally/technologically behind represents the dichotomous variable classifying each country into low/high countries. In contrast, the development/technology level uses the continuous measure instead

Source: By authors

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