Impacts of credit constraints on innovation propensity and innovation performance: evidence from China and India

Figures & data

Table 1. Sample distribution, firm sales, and new product sales.

Firm type	Firm number	Average sales (mil. LCU)	Average sales share of new products (%)
	China
Credit unconstrained firms	694	259	12.6
with product innovation	408	352	21.4
with process innovation	544	280	14.9
with organizational innovation	417	379	16.0
Credit constrained firms	999	169	9.45
with product innovation	364	178	25.9
with process innovation	535	223	14.2
with organizational innovation	365	225	14.5
Whole sample	1693	206	10.7
	India
Credit unconstrained firms	436	1134	10.3
with product innovation	299	1446	12.7
with process innovation	275	1206	11.9
with organizational innovation	212	896	8.71
Credit constrained firms	2255	559
with product innovation	1340	695	9.48
with process innovation	1394	670	9.86
with organizational innovation	1278	625	9.84
Whole sample	2691	653	9.61

Notes: LCU means local currency units, i.e., Yuan for China and Rupee for India.

Table 2. Variable definitions and descriptive statistics.

		China		India
Variable	Definition	Mean	SD	Mean	SD
New-Product	Dummy variable (= 1 for firms with new products, and 0 otherwise)	0.456	0.498	0.609	0.488
New-Process	Dummy variable (= 1 for firms with new products, and 0 otherwise)	0.637	0.481	0.620	0.485
Organizational	Dummy variable (= 1 for firms with new products, and 0 otherwise)	0.462	0.499	0.554	0.497
Sales (in logarithm)	The value of sales in Yuan for China and Rupee for India	16.91	1.674	18.068	1.953
Share (in %)	Sales share of new products over total turnover	10.73	17.57	9.614	21.39
Credit-Constraints	Dummy variable (= 1 for constrained firms, and 0 otherwise)	0.590	0.492	0.838	0.369
Size-Medium	Dummy variable (=1 for firms with employee numbers: ≥20 and ≤99, and 0 otherwise)	0.405	0.491	0.459	0.498
Size-Large	Dummy variable (=1 for Employee numbers: ≥100, and 0 otherwise)	0.467	0.499	0.269	0.444
High-tech	Dummy variable (= 1 for firms under the Standard Industrial Classification (SIC): 23–35), and 0 otherwise)	0.696	0.460	0.709	0.455
Firm-Age	Firms age in number of years	14.07	8.257	20.09	14.74
Foreign-Ownership	Dummy variable (=1 Firms with foreign investors, and 0 otherwise)	0.074	0.262	0.010	0.102
Group	Dummy variable (= 1 for firms that are part of a larger establishment, and 0 otherwise)	0.112	0.315	0.768	0.422
Export-Experience	Years since this establishment started exports	3.171	5.211	2.953	6.907
Manager-Experience	Manager experience in years	16.94	7.564	14.68	9.583
Worker-Skilled (in %)	Percentage of skilled production workers	44.18	24.87	64.03	21.53
Worker-Education (in %)	Percentage of workers who completed secondary school	50.45	27.81	49.33	29.05
Over-Competition	Dummy variable (= 1 for firms with competitors: ‘too many to count’, and 0 otherwise))	0.654	0.476	0.380	0.486
Location: Big-City	Dummy variable (= 1 for city with population over 1 million, and 0 otherwise)	0.982	0.132	0.326	0.469

Table 3. Correlation matrix.

Variable	Credit-Constraints	New-Product	New-Process	Organizational	Share	Sales
	China
Credit-Constraints	1
New-Product	−0.221	1
New-Process	−0.254	0.424	1
Organizational	−0.232	0.327	0.322	1
Share	−0.088	0.667	0.289	0.242	1
Sales	−0.204	0.184	0.135	0.255	0.091	1
	India
Credit-Constraints	1
New-Product	−0.069	1
New-Process	−0.010	0.283	1
Organizational	0.060	0.227	0.423	1
Share	−0.014	0.125	0.034	0.003	1
Sales	−0.103	0.152	0.125	0.059	0.086	1

Table 4. Mean difference test of variables for unconstrained and constrained firms.

	India
	Mean of		Mean difference	Mean of		Mean difference
Variable	Unconstrained firms	Constrained firms		Unconstrained firms	Constrained firms
New-Product	0.588	0.364	0.224	0.686	0.594	0.092
New-Process	0.784	0.536	0.248	0.631	0.618	0.013
Organizational	0.601	0.365	0.235	0.486	0.567	−0.081
Sales	17.32	16.63	0.695	18.53	17.98	0.546
Share	12.59	9.438	3.147	10.31	9.478	0.836
Size-Medium	0.375	0.426	−0.052	0.459	0.459	0.000
Size-Large	0.559	0.402	0.157	0.183	0.286	−0.102
High-tech	0.719	0.681	0.038	0.693	0.712	−0.019
Firm-Age (years)	14.98	13.44	1.543	20.42	20.03	0.388
Foreign-Ownership	0.098	0.057	0.041	0.025	0.008	0.018
Group	0.112	0.111	0.001	0.734	0.774	−0.040
Export-Experience	4.465	2.271	2.194	3.842	2.781	1.061
Manager-Experience	17.95	16.25	1.706	15.18	14.58	0.606
Worker-Skilled	42.82	45.13	−2.312	61.70	64.48	−2.785
Worker-Education	52.43	49.07	3.360	52.97	48.63	4.346
Over-Competition	0.575	0.709	−0.134	0.390	0.378	0.012
Location: Big-City	0.994	0.974	0.020	0.319	0.328	−0.009

Notes: ^{***, **}, and * indicate significant at the 0.01, 0.05 and 0.10 level, respectively.

Table 5. Estimation results of Model A for China.

Variable	Regression 1	Regression 2	Regression 3
Dependent variable	New-Product	New-Process	Organizational
Size-Medium	0.055	0.123 ***	0.1504***
	[0.0425]	[0.0358]	[0.0449]
Size-Large	0.1027**	0.1252***	0.2435***
	[0.0427]	[0.0374]	[0.0435]
High-tech	0.0508*	0.0255	0.0721**
	[0.0278]	[0.0267]	[0.0281]
Firm-Age	-0.003*	-0.0053***	0.0019
	[0.0017]	[0.0016]	[0.0018]
Foreign-Ownership	-0.009	0.0549	0.0828*
	[0.0501]	[0.0477]	[0.0513]
Group	0.2246***	0.0914**	0.1725***
	[0.0397]	[0.0370]	[0.0413]
Export-Experience	0.0107***	0.0046	0.007***
	[0.0027]	[0.0026]	[0.0027]
Manager-Experience	0.0016	0.006***	-0.0025
	[0.0018]	[0.0018]	[0.0018]
Worker-Skilled	0.0005	0.0012**	-0.0014***
	[0.0005]	[0.0005]	[0.0005]
Worker-Education	0.0008*	0.0005	0.0008
	[0.0005]	[0.0004]	[0.0005]
Over-Competition	0.0205	-0.0508**	-0.0381
	[0.0276]	[0.0261]	[0.0280]
Location: Big-City	-0.0352	-0.3086***	0.2461***
	[0.0986]	[0.0333]	[0.0879]
Credit-Constraints (CC)	-0.2003***	-0.2305***	-0.1883***
	[0.0259]	[0.0234]	[0.0262]
AIC	2198	2217	2149
Observations	1693	1693	1693

Notes: ^{***, **}, and * indicate significant at the 0.01, 0.05 and 0.10 level, respectively. Standard errors are in parenthesis.

Table 6. Estimation results of Model A for India.

Variable	Regression 3
Variable	Regression 1	Regression 2	Regression 3
Dependent variable	New-Product	New-Process	Organizational
Size-Medium	-0.0609**	0.0096	0.0658**
	[0.0264]	[0.0260]	[0.0268]
Size-Large	-0.1676***	-0.0863***	-0.0076
	[0.0308]	[0.0305]	[0.0311]
High-tech	0.0148	0.0354*	0.0408*
	[0.0217]	[0.0217]	[0.0226]
Firm-Age	-0.0001	0.0002	-0.0016**
	[0.0008]	[0.0008]	[0.0008]
Foreign-Ownership	0.2582***	0.2423***	0.1731**
	[0.0694]	[0.0709]	[0.0899]
Group	0.0069	-0.0871***	-0.203***
	[0.0250]	[0.0237]	[0.0234]
Export-Experience	0.0015	0.0055***	0.0036**
	[0.0016]	[0.0017]	[0.0017]
Manager-Experience	0.0025**	0.0041***	-0.0016
	[0.0011]	[0.0012]	[0.0012]
Worker-Skilled	0.0042***	0.0018***	0.0041***
	[0.0005]	[0.0005]	[0.0005]
Worker-Education	0.0009***	0.0009**	0.0016***
	[0.0004]	[0.0004]	[0.0004]
Over-Competition	-0.0494**	-0.1312***	-0.1354***
	[0.0208]	[0.0206]	[0.0214]
Location: Big-City	-0.1528***	-0.1928***	-0.1376***
	[0.0220]	[0.0219]	[0.0226]
Credit-Constraints (CC)	-0.0806***	0.0119	0.1024***
	[0.0257]	[0.0269]	[0.0281]
AIC	3380	3325	3386
Observations	2691	2691	2691

Notes: ^{***, **,} and * indicate significant at the 0.01, 0.05 and 0.10 level, respectively. Standard errors are in parenthesis.

Table 7. Estimation results of Model B for China.

Variable	Regression 1	Regression 2	Regression 3
Dependent variable	Share
Intercept	−36.2263***	−39.3886***	−17.2927**
	[8.2370]	[8.0603]	[7.9576]
Size-Medium	2.9449	4.2843	5.7693*
	[3.0603]	[3.0856]	[3.0723]
Size-Large	3.0182	5.6112*	5.4017*
	[3.1113]	[3.1205]	[3.1219]
High-tech	2.4519	3.2637*	2.3962
	[1.9473]	[1.9645]	[1.9848]
Firm-Age	−0.1734	−0.1266	−0.3346***
	[0.1205]	[0.1204]	[0.1239]
Foreign-Ownership	0.5788	1.1942	1.552
	[3.2535]	[3.2966]	[3.3461]
Group	6.6851**	8.0736***	7.7526***
	[2.6745]	[2.6983]	[2.7557]
Export-Experience	0.4807***	0.5468***	0.5768***
	[0.1730]	[0.1745]	[0.1780]
Manager-Experience	0.0206	−0.0093	0.1553
	[0.1236]	[0.1246]	[0.1259]
Worker-Skilled	−0.052	−0.0781**	−0.0051
	[0.0356]	[0.0357]	[0.0362]
Worker-Education	0.0674**	0.0762**	0.0712**
	[0.0322]	[0.0325]	[0.0329]
Over-Competition	0.3938	0.0227	−0.8774
	[1.8721]	[1.8881]	[1.9166]
Location: Big-City	−0.3009	3.2741	−7.9899
	[6.5729]	[6.6260]	[6.8213]
New-Process	28.9819***	34.074***
	[2.2724]	[2.4718]
Organizational	12.0864***
	[1.8998]		21.9376***
Credit-Constraints (CC)	−1.5782		[2.2535]
	[1.8695]
New-Process: CC		−2.3994
		[2.0816]
Organizational: CC			−5.5664**
			[2.5184]
Log-likelihood	−3251	−4095	−4000
Observations	1693	1693	1693

Notes: ^{***, **}, and * indicate significant at the 0.01, 0.05 and 0.10 level, respectively. Standard errors are in parenthesis.

Table 8. Estimation results of Model B for India.

Variable	Regression 1	Regression 2	Regression 3
Dependent variable	Share
Intercept	−67.0585***	−65.68***	−62.992***
	[10.0554]	[9.3780]	[9.2731]
Size-Medium	0.5701	0.7821	0.5618
	[4.3300]	[4.3187]	[4.3224]
Size-Large	−13.5745**	−13.4249**	−14.2042***
	[5.3001]	[5.2843]	[5.2761]
High-tech	−1.2983	−1.2284	−1.2488
	[3.7287]	[3.7235]	[3.7235]
Firm-Age	−0.0981	−0.1023	−0.0941
	[0.1287]	[0.1286]	[0.1287]
Foreign-Ownership	12.4725	11.3117	14.1186
	[15.3728]	[15.4247]	[15.3388]
Group	−1.8027	−2.1175	−1.9693
	[4.1984]	[4.1561]	[4.1925]
Export-Experience	0.5941**	0.5889**	0.6267**
	[0.2559]	[0.2559]	[0.2555]
Manager-Experience	0.5717***	0.5601***	0.6063***
	[0.1928]	[0.1923]	[0.1921]
Worker-Skilled	0.2044**	0.2179***	0.2081**
	[0.0845]	[0.0835]	[0.0844]
Worker-Education	−0.0113	−0.0115	−0.0092
	[0.0634]	[0.0633]	[0.0634]
Over-Competition	1.075	0.9136	0.4639
	[3.6187]	[3.6045]	[3.6078]
Location: Big-City	−8.7382**	−9.1895**	−9.6516**
	[3.8988]	[3.8820]	[3.8686]
New-Process	8.3465**	12.4452**
	[4.0650]	[5.9999]
Organizational	2.6895		2.1784
	[3.9760]		[6.5836]
Credit-Constraints (CC)	0.9419
	[4.6590]
New-Process: CC		−3.6363
		[5.6019]
Organizational: CC			4.3239
			[6.3348]
Log-likelihood	−4359	−4359	−4361
Observations	2691	2691	2691

Notes: ^{***, **}, and * indicate significant at the 0.01, 0.05 and 0.10 level, respectively. Standard errors are in parenthesis.

Table 9. Estimation results of Model C for China.

Variable	Regression 1	Regression 2	Regression 3	Regression 4
Dependent variable	Sales
Intercept	14.1295***	13.9943***	13.9803***	13.9947***
	[0.2999]	[0.2933]	[0.3009]	[0.2919]
Size-Medium	1.1336***	1.168***	1.159***	1.147***
	[0.0943]	[0.0948]	[0.0951]	[0.094]
Size-Large	2.4685***	2.5261***	2.519***	2.4855***
	[0.1016]	[0.1021]	[0.1025]	[0.101]
High-tech	0.2616***	0.2768***	0.2807***	0.2706***
	[0.0649]	[0.0652]	[0.0652]	[0.0649]
Firm-Age	0.012***	0.0123***	0.0125***	0.0111**
	[0.0046]	[0.0046]	[0.0048]	[0.0047]
Foreign-Ownership	−0.0209	5.00E-04	−0.002	−0.0182
	[0.114]	[0.1146]	[0.1144]	[0.1136]
Group	0.8519***	0.8694***	0.903***	0.8737***
	[0.1337]	[0.1329]	[0.1322]	[0.1334]
Export-Experience	0.0188***	0.0199***	0.0216***	0.02***
	[0.0068]	[0.0068]	[0.0068]	[0.0067]
Manager-Experience	0.021***	0.0208***	0.0205***	0.0213***
	[0.0044]	[0.0044]	[0.0044]	[0.0044]
Worker-Skilled	−0.0029**	−0.0034***	−0.0034***	−0.003**
	[0.0013]	[0.0013]	[0.0013]	[0.0013]
Worker-Education	−0.0007	−0.0007	−0.0006	−0.0007
	[0.0012]	[0.0012]	[0.0012]	[0.0012]
Over-Competition	−0.1073	−0.1257*	−0.1131*	−0.1051
	[0.069]	[0.0684]	[0.069]	[0.0685]
Location: Big-City	0.5037**	0.568**	0.576**	0.54**
	[0.2424]	[0.2466]	[0.2504]	[0.2446]
New-Product	0.1176*	0.323***
	[0.0707]	[0.0786]
New-Process	−0.0188		0.2486***
	[0.0726]		[0.0773]
Organizational	0.2272***			0.4117***
	[0.0638]			[0.0783]
Credit-Constraints (CC)	−0.1573**
	[0.064]
New-Product: CC		−0.2461***
		[0.0921]
New-Process: CC			−0.2188***
			[0.0769]
Organizational: CC				−0.2639***
				[0.0928]
Adj.R^2	0.4533	0.45	0.4483	0.4535
Observations	1693	1693	1693	1693

Notes: ^{***, **}, and * indicate significant at the 0.01, 0.05 and 0.10 level, respectively. Standard errors are in parenthesis.

Table 10. Estimation results of Model C for India.

Variable	Regression 1	Regression 2	Regression 3	Regression 4
Dependent variable	Sales
Intercept	19.9348***	19.7782***	19.8215***	19.9242***
	[0.1538]	[0.1421]	[0.1449]	[0.1417]
Size-Medium	−1.803***	−1.8173***	−1.8283***	−1.8176***
	[0.0735]	[0.0731]	[0.0735]	[0.0738]
Size-Large	−3.0181***	−3.0301***	−3.0541***	−3.0572***
	[0.0848]	[0.0849]	[0.0842]	[0.0845]
High-tech	0.2069***	0.1999***	0.2001***	0.2078***
	[0.0611]	[0.061]	[0.0611]	[0.0611]
Firm-Age	−5.00E-04	−1.00E-04	−2.00E-04	−4.00E-04
	[0.0023]	[0.0023]	[0.0023]	[0.0023]
Foreign-Ownership	0.6723**	0.6528**	0.6897**	0.726**
	[0.3348]	[0.336]	[0.337]	[0.3393]
Group	−0.5704***	−0.5353***	−0.5316***	−0.5671***
	[0.0716]	[0.0708]	[0.0713]	[0.0718]
Export-Experience	0.0279***	0.0278***	0.0277***	0.0283***
	[0.0045]	[0.0045]	[0.0046]	[0.0046]
Manager-Experience	−0.003	−0.0022	−0.0021	−0.0022
	[0.0035]	[0.0035]	[0.0035]	[0.0035]
Worker-Skilled	−0.0016	−0.0023	−0.0019	−0.0013
	[0.0014]	[0.0014]	[0.0013]	[0.0014]
Worker-Education	0.0038 ***	0.0037 ***	0.0037 ***	0.0040 ***
	[0.0011]	[0.0011]	[0.0011]	[0.0011]
Over-Competition	0.0513	0.067	0.0706	0.0444
	[0.0585]	[0.0578]	[0.0588]	[0.0581]
Location: Big-City	0.032	0.0436	0.0277	0.0015
	[0.064]	[0.064]	[0.064]	[0.0632]
New-Product	0.1424**	0.2619***
	[0.0607]	[0.094]
New-Process	0.0946		0.1275
	[0.0653]		[0.0991]
Organizational	−0.2321***			−0.0826
	[0.0647]			[0.1101]
Credit-Constraints (CC)	−0.1251*
	[0.0748]
New-Product: CC		−0.1605*
		[0.0899]
New-Process: CC			−0.1064
			[0.0943]
Organizational: CC				−0.1124
				[0.105]
Adj.R^2	0.4649	0.4626	0.4613	0.4631
Observations	2691	2691	2691	2691

Notes: ^{***, **}, and * indicate significant at the 0.01, 0.05 and 0.10 level, respectively. Standard errors are in parenthesis.