Enterprises’ national innovation system performance in Egypt, Côte d’Ivoire and Cameroon

Figures & data

Figure 1. Representation of the Quintuple Helix model of innovation. Source: Authors’ construction, 2019.

Chart 1. Overall representation of innovative enterprises. Source: Authors using data from WBES-2016.

Table 1. m-logit regression results following the ‘Product Innovation’ mode.

Variables	Egypt		Côte d’Ivoire		Cameroon
	InvPrd	RRR	InvPrd	RRR	InvPrd	RRR
RD	1.452***	4.271***	0.209	1.232	0.284	1.328
	(0.265)	(1.134)	(0.488)	(0.601)	(0.407)	(0.541)
Fperso	1.248***	3.483***	0.417	1.517	0.196	1.217
	(0.216)	(0.752)	(0.262)	(0.398)	(0.267)	(0.325)
Dlexploi	0.002	1.002	0.022	1.022	0.025	1.025
	(0.001)	(0.001)	(0.015)	(0.016)	(0.025)	(0.026)
Dinterne	−0.009***	0.991***	0.002	1.002	0.006	1.006
	(0.003)	(0.003)	(0.005)	(0.005)	(0.006)	(0.006)
TD	−0.002	0.998	−0.001	0.999	0.002	1.002
	(0.002)	(0.002)	(0.003)	(0.003)	(0.003)	(0.003)
Constant	−2.353***	0.095***	−2.087**	0.124**	−2.049**	0.129**
	(0.362)	(0.034)	(0.820)	(0.102)	(0.914)	(0.118)
Pseudo R^2	0.1240		0.0561		0.0285
Prob > chi^2	0.000		0.0001		0.1237
LR chi^2	218.83		43.37		21.43
Observations	1814		361		361

Note: Standard errors are expressed in parentheses, level of significance ***p < 0.01, **p < 0.05, *p < 0.10.

Source: Authors’ estimates on STATA from WBES-2016 data.

Table 2. m-logit regression results following the ‘Process Innovation’ mode.

Variables	Egypt		Côte d’Ivoire		Cameroon
	InvPrc	RRR	InvPrc	RRR	InvPrc	RRR
RD	1.269***	3.557***	−0.219	0.803	−12.824	0.000
	(0.479)	(1.705)	(1.070)	(0.859)	(554.781)	(0.001)
Fperso	1.022***	2.777***	0.299	1.348	0.225	1.252
	(0.384)	(1.065)	(0.490)	(0.661)	(0.653)	(0.817)
Dlexploi	0.001	1.001	0.028*	1.028*	0.009	1.009
	(0.003)	(0.003)	(0.016)	(0.017)	(0.063)	(0.064)
Dinterne	−0.009*	0.991*	−0.008	0.992	−0.016*	0.984*
	(0.006)	(0.006)	(0.007)	(0.007)	(0.009)	(0.009)
TD	−0.007*	0.993*	−0.002	0.998	0.002	1.002
	(0.004)	(0.004)	(0.006)	(0.006)	(0.007)	(0.007)
Constant	−3.020***	0.049***	−2.893***	0.055***	−1.754	0.173
	(0.581)	(0.028)	(0.977)	(0.054)	(1.893)	(0.328)
Pseudo R^2	0.1240		0.0561		0.0285
Prob > chi^2	0.000		0.0001		0.1237
LR chi^2	218.83		43.37		21.43
Observations	1814		361		361

Note: Standard errors are expressed in parentheses, level of significance ***p < 0.01, **p < 0.05, *p < 0.10.

Source: Authors’ estimates on STATA from WBES-2016 data.

Table 3. m-logit regression results following the ‘Product and Process Innovation’ mode.

Variables	Egypt		Côte d’Ivoire		Cameroon
	InvPrdPrc	RRR	InvPrdPrc	RRR	InvPrdPrc	RRR
RD	1.706***	5.505***	1.792***	6.001***	0.727	2.068
	(0.305)	(1.677)	(0.444)	(2.665)	(0.493)	(1.019)
Fperso	1.764***	5.833***	0.957***	2.604***	0.787**	2.198**
	(0.284)	(1.654)	(0.370)	(0.965)	(0.372)	(0.816)
Dlexploi	0.004**	1.004**	−0.010	0.991	−0.024	0.977
	(0.002)	(0.002)	(0.018)	(0.018)	(0.041)	(0.040)
Dinterne	−0.002	0.998	−0.002	0.998	0.003	1.003
	(0.005)	(0.005)	(0.007)	(0.007)	(0.008)	(0.008)
TD	0.013***	1.014***	0.007*	1.007*	0.006	1.006
	(0.005)	(0.005)	(0.004)	(0.004)	(0.004)	(0.004)
Constant	−5.158***	0.006***	−2.099**	0.123**	−1.887	0.152
	(0.690)	(0.004)	(0.988)	(0.121)	(1.373)	(0.208)
Pseudo R^2	0.1240		0.0561		0.0285
Prob > chi^2	0.000		0.0001		0.1237
LR chi^2	218.83		43.37		21.43
Observations	1814		361		361

Note: Standard errors are expressed in parentheses, level of significance ***p < 0.01, **p < 0.05, *p < 0.10.

Source: Authors’ estimates on STATA from WBES-2016 data.

Table A1. Robustness check with controls for ‘Product Innovation’.

Variables	Egypt	Côte d’Ivoire	Cameroon
	InvPrd	InvPrd	InvPrd
RD	1.544***	0.064	0.439
	(0.274)	(0.503)	(0.434)
Fperso	1.320***	0.198	0.009
	(0.225)	(0.280)	(0.284)
Dlexploi	0.003*	0.029*	0.035
	(0.001)	(0.017)	(0.027)
Dinter	−0.008**	0.006	0.003
	(0.004)	(0.006)	(0.007)
TD	−0.002	−0.002	0.001
	(0.003)	(0.003)	(0.003)
Local	−0.373*	−0.397	−1.248***
	(0.216)	(0.309)	(0.299)
Size	0.000	0.003*	0.005*
	(0.000)	(0.002)	(0.003)
Foreign	0.010***	0.001	−0.001
	(0.004)	(0.004)	(0.006)
HighSchool	−0.004	0.009**	0.001
	(0.003)	(0.004)	(0.003)
Rservices	0.237	−0.107	0.402
	(0.439)	(0.359)	(0.348)
Oservices	−0.034	0.082	0.211
	(0.257)	(0.334)	(0.322)
Constant	−2.096***	−2.779***	−1.901*
	(0.453)	(0.928)	(1.013)
Pseudo R^2	0.1619	0.0842	0.0765
Prob > chi^2	0.000	0.001	0.005
LR chi^2	285.64	65.08	57.48
Observations	1814	361	361

Note: Standard errors are expressed in parentheses, level of significance ***p < 0.01, **p < 0.05, *p < 0.10.

Source: Authors’ estimates on STATA from WBES-2016 data.

Table A2. Robustness check with controls for ‘Process Innovation’.

Variables	Egypt	Côte d’Ivoire	Cameroon
	InvPrc	InvPrc	InvPrc
RD	1.246**	−0.405	−16.873
	(0.518)	(1.085)	(4,663.716)
Fperso	1.100***	0.162	0.100
	(0.408)	(0.526)	(0.722)
Dlexploi	0.001	0.034*	0.042
	(0.003)	(0.018)	(0.088)
Dinter	−0.005	−0.003	−0.025**
	(0.006)	(0.008)	(0.011)
TD	−0.007*	−0.004	0.003
	(0.004)	(0.006)	(0.007)
Local	−0.496	−0.403	−1.065
	(0.377)	(0.572)	(0.784)
Size	0.000**	0.002	−0.018
	(0.000)	(0.003)	(0.016)
Foreign	0.011	−0.003	−1.194
	(0.006)	(0.007)	(65.957)
HighSchool	−0.009	0.008	0.002
	(0.005)	(0.007)	(0.009)
Rservices	0.493	−1.263	−1.154
	(0.677)	(0.876)	(0.802)
Oservices	0.121	0.313	−1.164
	(0.442)	(0.573)	(0.765)
Constant	−2.719***	−3.399***	−0.392
	(0.743)	(1.131)	(2.486)
Pseudo R^2	0.1619	0.0842	0.0765
Prob > chi^2	0.000	0.001	0.005
LR chi^2	285.64	65.08	57.48
Observations	1814	361	361

Note: Standard errors are expressed in parentheses, level of significance ***p < 0.01, **p < 0.05, *p < 0.10.

Source: Authors’ estimates on STATA from WBES-2016 data.

Table A3. Robustness check with controls for ‘Product and Process Innovation’.

Variables	Egypt	Côte d’Ivoire	Cameroon
	InvPrdPrc	InvPrdPrc	InvPrdPrc
RD	1.890***	1.740***	0.587
	(0.337)	(0.459)	(0.536)
Fperso	2.037***	0.875**	0.608
	(0.306)	(0.389)	(0.389)
Dlexploi	0.003	0.006	−0.023
	(0.002)	(0.019)	(0.042)
Dinter	−0.000	0.003	0.006
	(0.006)	(0.008)	(0.009)
TD	0.008	0.006	0.005
	(0.005)	(0.004)	(0.004)
Local	−1.063***	−0.368	−0.522
	(0.284)	(0.439)	(0.395)
Size	−0.000	0.004**	0.005**
	(0.000)	(0.002)	(0.003)
Foreign	0.009	0.005	0.009
	(0.006)	(0.005)	(0.007)
HighSchool	−0.013***	0.003	0.004
	(0.004)	(0.005)	(0.005)
Rservices	−0.915	−0.267	−0.103
	(1.043)	(0.524)	(0.522)
Oservices	−1.342**	−0.047	−0.028
	(0.549)	(0.466)	(0.431)
Constant	−3.425***	−3.110***	−2.207
	(0.767)	(1.124)	(1.530)
Pseudo R^2	0.1619	0.0842	0.0765
Prob > chi^2	0.000	0.001	0.005
LR chi^2	285.64	65.08	57.48
Observations	1814	361	361

Note: Standard errors are expressed in parentheses, level of significance ***p < 0.01, **p < 0.05, *p < 0.10.

Source: Authors’ estimates on STATA from WBES-2016 data.

Table A4. Robustness check with controls and subsidies only for Egypt.

Variables	Egypt
	InvPrd	InvPrc	InvPrdPrc
RD	1.547***	1.242**	1.882***
	(0.275)	(0.527)	(0.338)
Fperso	1.285***	1.124***	2.034***
	(0.227)	(0.408)	(0.306)
Dlexploi	0.002*	0.001	0.003
	(0.001)	(0.003)	(0.002)
Dinter	−0.007**	−0.006	−0.000
	(0.004)	(0.006)	(0.006)
TD	−0.002	−0.007*	0.008
	(0.003)	(0.004)	(0.005)
Local	−0.345	−0.532	−1.064***
	(0.217)	(0.379)	(0.285)
Size	0.000	0.000**	−0.000
	(0.000)	(0.000)	(0.000)
Foreign	0.010***	0.010	0.009
	(0.004)	(0.006)	(0.006)
HighSchool	−0.005	−0.009	−0.013***
	(0.003)	(0.005)	(0.004)
Rservices	0.227	0.516	−0.898
	(0.444)	(0.675)	(1.042)
Oservices	−0.032	0.123	−1.335**
	(0.258)	(0.441)	(0.548)
Subs	0.794*	−16.002	−0.065
	(0.460)	(2723.285)	(0.795)
Constant	−2.134***	−2.675***	−3.426***
	(0.454)	(0.744)	(0.769)
Pseudo R^2	0.165
Prob > chi^2	0.000
LR chi^2	291.13
Observations	1814

Note: Standard errors are expressed in parentheses, level of significance ***p < 0.01, **p < 0.05, *p < 0.10.

Source: Authors’ estimates on STATA from WBES-2016 data.

Table A5. Regression results with instrumental variables.

Variables	Egypt	Côte d’Ivoire	Cameroon
RD	0.833**	0.830	1.733
	(0.351)	(1.538)	(1.584)
Fperso	0.373***	0.218	−0.285
	(0.093)	(0.234)	(0.505)
Dlexploi	0.001**	0.009	−0.023
	(0.000)	(0.020)	(0.028)
Dinterne	−0.001	−0.003	−0.007
	(0.001)	(0.003)	(0.005)
TD	0.000	0.001	−0.001
	(0.001)	(0.002)	(0.002)
Constant	0.140	0.378	1.918**
	(0.096)	(1.037)	(0.891)
Observations	1173	106	102
R-squared	0.155	0.058	0
Pob. Durbin	0.5872	0.8934	0.3731
Prob. Wu-Hausman	0.5884	0.8973	0.3904

Note: Standard errors are expressed in parentheses, level of significance ***p < 0.01, **p < 0.05, *p < 0.10.

Source: Authors’ estimates on STATA from WBES-2016 data.

Table A6. Firms’ distribution by industry sector.

	Industry	Egypt	Cote d’Ivoire	Cameroon
Manufacturing	Extractives	5	0	0
	Food	199	30	20
	Tobacco	4	0	0
	Textiles	56	0	2
	Garments	76	14	7
	Leather	99	2	0
	Wood	40	11	8
	Paper	43	1	2
	Publishing, printing, and Recorded media	19	7	15
	Refined petroleum product	8	0	2
	Chemicals	124	9	6
	Plastics & rubber	123	0	6
	Non-metallic mineral products	129	1	0
	Basic metals	20	2	4
	Fabricated metal products	113	10	9
	Machinery and equipment (29–30)	60	2	5
	Electronics (31–32)	9	2	2
	Precision instruments	16	0	0
	Transport machines (34–35)	6	0	0
	Furniture	20	8	13
	Recycling	28	0	1
	Sub-total Manufactures	1193	106	102
Retail services	Retail	113	106	117
Other services	Wholesale	67	40	33
	IT	68	9	10
	Hotel and restaurants: section H	78	16	32
	Construction Section F:	95	20	20
	Services of motor vehicles	22	40	24
	Transport Section I: (60–64)	106	24	23
	Travel Agencies	49	0	0
	Real estate	19	0	0
	Sub-total Others services	508	138	153
	Total	1814	361	361

Source: Authors’ production based on WBES-2016 data.

Table A7. Descriptive statistics for Egypt.

Variables	Questions from Enterprises Survey	Obs.	Mean	S.D.	Min	Max
Innovation	The multinomial variable Innovation is constructed from 2 variables: h1 and h5 in the Enterprises Survey questionnaire. The question relating to these variables is: In the last three years has the establishment introduced new products/services (h1), new processes (h5)?	1814	0.215	0.659	0	3
R&D	In the last fiscal year, did the establishment spend on R&D (excluding market research)? This is a binary variable taking the value 1 if the company invests in R&D and 0 otherwise.	1814	0.076	0.264	0	1
Fperso	Has the establishment introduced formal training programs for permanent full-time employees in the last fiscal year? This variable is also binary taking the value 1 if the company carries out training for staff and 0 otherwise.	1814	0.210	0.407	0	1
Dlexploi	How many days did it take to get your operating license? Days are between 0 and 90.	1814	34.065	45.588	0	995
Dinterne	In the last fiscal year, what was the establishment’s share in the national sales? Sales shares are in percentage.	1814	90.277	24.080	0	100
TD	What is the percentage of the land occupied by the establishment (owned by the establishment)? Lands shares are in percentage.	1814	72.669	44.248	0	100
Local	Is the establishment located in the main business city? This is a binary variable taking the value 1 if the establishment is located in the main business city and 0 otherwise.	1814	0.658	0.474	0	1
Sector	The establishment industry sector. This is a categorical variable taking the value 1 for Manufacturing, 2 for Retail services and 3 for other services.	1814	1.639	0.896	1	3
Size	What is the number of Permanent Full-Time Employees at end of 3 fiscal years ago? This is a numerical variable.	1814	170.793	618.168	0	15000
Foreign	What is the percentage owned by private foreign individuals, companies or organizations? This is a numerical variable.	1814	4.448	18.53	0	100
HighSchool	This is a quantitative variable indicating the % Of full time workers completed high school within the establishment.	1814	67.998	32.302	0	100
Subs	Does the establishment received direct subsidies (including wage, investment, other) over last 3 years? This is a binary variable taking the value 1 if the establishment received direct subsidies and 0 otherwise	1814	0.02	0.141	0	1

Source: Authors’ production based on WBES-2016 data.

Table A8. Descriptive statistics for Côte d’Ivoire.

Variables	Questions from Enterprises Survey	Obs.	Mean	S.D.	Min	Max
Innovation	The multinomial variable Innovation is constructed from 2 variables: h1 and h5 in the Enterprises Survey questionnaire. The question relating to these variables is: In the last three years has the establishment introduced new products/services (h1), new processes (h5)?	361	0.706	1.01	0	3
R&D	In the last fiscal year, did the establishment spend on R&D (excluding market research)? This is a binary variable taking the value 1 if the company invests in R&D and 0 otherwise.	361	0.1	0.3	0	1
Fperso	Has the establishment introduced formal training programs for permanent full-time employees in the last fiscal year? This variable is also binary taking the value 1 if the company carries out training for staff and 0 otherwise.	361	0.424	0.495	0	1
Dlexploi	How many days did it take to get your operating license? Days are between 0 and 90.	361	42.008	20.336	0	365
Dinterne	In the last fiscal year, what was the establishment’s share in the national sales? Sales shares are in percentage.	361	90.224	25.685	0	100
TD	What is the percentage of the land occupied by the establishment (owned by the establishment)? Lands shares are in percentage.	361	24.413	42.154	0	100
Local	Is the establishment located in the main business city? This is a binary variable taking the value 1 if the establishment is located in the main business city and 0 otherwise.	361	0.681	0.467	0	1
Sector	The establishment industry sector. This is a categorical variable taking the value 1 for Manufacturing, 2 for Retail services and 3 for other services.	361	2.114	0.831	1	3
Size	What is the number of Permanent Full-Time Employees at end of 3 fiscal years ago? This is a numerical variable.	361	43.102	115.294	0	1170
HighSchool	This is a quantitative variable indicating the % Of full time workers completed high school within the establishment.	361	28.346	36.484	0	100
Foreign	What is the percentage owned by private foreign individuals, companies or organizations? This is a numerical variable.	361	20.327	37.736	0	100

Source: Authors’ production based on WBES-2016 data.

Table A9. Descriptive statistics for Cameroon.

Variables	Questions from Enterprises Survey	Obs.	Mean	S.D.	Min	Max
Innovation	The multinomial variable Innovation is constructed from 2 variables: h1 and h5 in the Enterprises Survey questionnaire. The question relating to these variables is: In the last three years has the establishment introduced new products/services (h1), new processes (h5)?	361	0.693	0.973	0	3
R&D	In the last fiscal year, did the establishment spend on R&D (excluding market research)? This is a binary variable taking the value 1 if the company invests in R&D and 0 otherwise.	361	0.102	0.304	0	1
Fperso	Has the establishment introduced formal training programs for permanent full-time employees in the last fiscal year? This variable is also binary taking the value 1 if the company carries out training for staff and 0 otherwise.	361	0.335	0.473	0	1
Dlexploi	How many days did it take to get your operating license? Days are between 0 and 90.	361	27.008	4.975	0	90
Dinterne	In the last fiscal year, what was the establishment’s share in the national sales? Sales shares are in percentage.	361	91.186	21.608	0	100
TD	What is the percentage of the land occupied by the establishment (owned by the establishment)? Lands shares are in percentage.	361	28.371	44.151	0	100
Local	Is the establishment located in the main business city? This is a binary variable taking the value 1 if the establishment is located in the main business city and 0 otherwise.	361	0.396	0.49	0	1
Sector	The establishment industry sector. This is a categorical variable taking the value 1 for Manufacturing, 2 for Retail services and 3 for other services.	361	2.1108	0.8158	1	3
Size	What is the number of Permanent Full-Time Employees at end of 3 fiscal years ago? This is a numerical variable.	361	31.378	74.615	0	1000
HighSchool	This is a quantitative variable indicating the % Of full time workers completed high school within the establishment.	361	36.2133	39.87956	0	100
Foreign	What is the percentage owned by private foreign individuals, companies or organizations? This is a numerical variable.	361	5.565	21.063	0	100

Source: Authors’ production based on WBES-2016 data.

Table A10. Correlation matrix.

Panel A: Correlation matrix for Egypt
	inno	RD	fperso	Dlexploi	dinterne	td	local	size	foreign	HighSchool	sector	subs
inno	1.00
RD	0.30***	1.00
fperso	0.28***	0.32***	1.00
dlexploi	0.05*	−0.00	−0.01	1.00
dinterne	−0.10***	−0.13***	−0.13***	0.01	1.00
td	0.06**	0.08***	0.09***	−0.03	−0.02	1.00
local	−0.13***	−0.01	−0.01	0.00	0.05*	−0.13***	1.00
size	0.13***	0.21***	0.21***	−0.02	−0.21***	0.09***	−0.04	1.00
foreign	0.09***	0.05	0.07**	−0.02	−0.19***	−0.06*	−0.04	0.10***	1.00
HighSchool	−0.04	0.12***	0.17***	−0.03	−0.05*	−0.02	0.18***	0.02	−0.00	1.00
sector	−0.10***	−0.06*	−0.01	−0.03	0.06**	−0.32***	0.25***	−0.08***	−0.05*	0.25***	1.00
subs	0.04	0.05*	0.12***	0.02	−0.11***	0.01	−0.04	0.10***	0.04	0.06*	−0.02	1.00

Source: Authors’ production based on WBES-2016 data.

Table A11. Correlation matrix.

Correlation matrix for Côte d’Ivoire
	inno	RD	fperso	dlexploi	dinterne	td	local	size	foreign	HighSchool	sector
inno	1.00
RD	0.23***	1.00
fperso	0.18***	0.11*	1.00
dlexploi	0.03	−0.08	0.04	1.00
dinterne	−0.03	−0.03	−0.04	0.02	1.00
td	0.10	0.06	0.14**	−0.06	0.05	1.00
local	−0.03	0.03	−0.09	0.01	0.09	−0.23***	1.00
size	0.20***	0.14**	0.12*	−0.02	−0.15**	0.11*	0.10	1.00
foreign	0.05	−0.04	0.04	0.00	−0.15**	−0.12*	0.06	0.11*	1.00
HighSchool	0.12*	0.10	0.22***	−0.00	−0.11*	−0.00	0.26***	0.15**	0.11*	1.00
sector	0.02	−0.05	0.16**	0.06	0.09	−0.01	0.06	−0.09	−0.04	0.18***	1.00

Source: Authors’ production based on WBES-2016 data.

Table A12. Correlation matrix.

Correlation matrix for Cameroon
	inno	RD	fperso	dlexploi	dinterne	td	local	size	foreign	HighSchool	sector
inno	1.00
RD	0.10	1.00
fperso	0.15**	0.21***	1.00
dlexploi	−0.01	−0.00	0.06	1.00
dinterne	−0.02	−0.03	−0.06	0.01	1.00
td	0.11*	0.06	0.19***	−0.03	−0.15**	1.00
local	−0.11*	0.08	−0.10	0.02	−0.16**	−0.01	1.00
size	0.14**	0.24***	0.16**	−0.01	−0.20***	0.23***	0.16**	1.00
foreign	0.09	0.06	0.11*	0.01	−0.08	0.02	0.01	0.12*	1.00
HighSchool	0.00	0.04	0.04	−0.10	−0.06	−0.08	0.25***	0.06	0.01	1.00
sector	−0.03	−0.07	0.06	−0.04	0.09	−0.02	0.01	−0.14**	0.01	0.01	1.00

Source: Authors’ production based on WBES-2016 data.