Toward Cleaner Production: Can Mobile Phone Technology Help Reduce Inorganic Fertilizer Application? Evidence Using a National Level Dataset
Abstract
:1. Introduction
2. Conceptual Framework of the Study
3. Materials and Methods
3.1. Study Area
3.2. Sampling and Data
3.3. Data Modeling
4. Results and Discussion
4.1. Baseline Outcomes: Effect on IF Usage
4.2. The Mediating Role of Human Capital
4.3. Policy Assessment: DID Method
4.4. Robustness Test: PSM-DID Model
4.5. Robustness Test-Two: Instrumental Variables Method (IVM)
5. Conclusions and Recommendations
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Variables Names | Description | Mean (S.D) |
---|---|---|
Inorganic fertilizer | Use of inorganic fertilizer (kg/ha) | 198.40 (36.98) |
Mobile phone | Whether the household uses mobile phone (1 = yes; 0 = no) | 0.17 (0.42) |
Age | Age of the respondent (year) | 43.16 (14.23) |
Health status | Health status of head 1 | 6.45 (2.83) |
Education | Education of head (year) | 5.63 (3.41) |
Household size | Household member (numbers) | 6.45 (2.83) |
Land area | Land area per capita (ha) | 2.85 (2.14) |
IT | Number of households using Internet technology | 2.85 (3.52) |
Income | Per capita income (Afghani) | 27,984.19 (41,846.61) |
Asset | Fixed assets produced per capita (Afghani) | 2572.16 (16,292.17) |
Cereal crop | Whether the cereal crops are the major product (1 = cereal income ratio 50%; 0 = ratios of cereals profits to farming profits fewer than 50%) | 0.55 (0.49) |
Agricultural Education | If the household received AEST (1= yes, 0= no) | 0.20 (0.41) |
Non-Agricultural Education | If the household received NAEST (1= yes, 0= no) | 0.42 (0.50) |
Explanatory Variables | Column (1) | S.E | Column (2) | S.E | Column (3) | S.E | Column (4) | S.E |
---|---|---|---|---|---|---|---|---|
Age | −0.002 | 0.082 | −0.005 | 0.082 | −0.002 | 0.082 | −0.006 | 0.082 |
Health status | 0.085 *** | 0.028 | 0.083 *** | 0.028 | 0.086 *** | 0.028 | 0.085 *** | 0.028 |
Education | 0.019 | 0.016 | 0.019 | 0.016 | 0.019 | 0.016 | 0.019 | 0.016 |
Household size | −0.015 | 0.007 | −0.015 | 0.007 | −0.014 | 0.008 | −0.014 | 0.008 |
Land area | −0.260 *** | 0.030 | −0.260 *** | 0.030 | −0.260 *** | 0.030 | −0.261 *** | 0.030 |
IT | 0.000 | 0.002 | 0.000 | 0.002 | −0.062 *** | 0.013 | −0.056 *** | 0.013 |
Income | 0.064 *** | 0.009 | 0.064 *** | 0.009 | 0.064 *** | 0.009 | 0.064 *** | 0.009 |
Asset | 0.088 *** | 0.006 | 0.088 *** | 0.006 | 0.089 *** | 0.006 | 0.088 *** | 0.006 |
Cereal crop | 2.573 *** | 0.041 | 2.529 *** | 0.042 | 2.447 *** | 0.049 | 2.419 *** | 0.049 |
Mobile phone | −0.126 ** | 0.053 | −0.355 *** | 0.075 | −0.117 ** | 0.053 | −0.321 *** | 0.352 |
Mobile phone× cereal crop | - | - | 0.395 *** | 0.091 | - | - | 0.352 *** | 0.092 |
IT× cereal crop | - | - | - | - | 0.063 *** | 0.013 | 0.058 *** | 0.013 |
Constant | 0.504 | 3.181 | 0.943 | 4.171 | 0.561 | 4.171 | 0.872 | 4.171 |
Individual effect | Yes | - | Yes | - | Yes | - | Yes | - |
Year effects | Yes | - | Yes | - | Yes | - | Yes | - |
Area dummies | Yes | - | Yes | - | Yes | - | Yes | - |
Observation numbers | 31,036 | - | 31,036 | - | 31,036 | - | 31,036 | - |
Group number | 7514 | - | 7514 | - | 7514 | - | 7514 | - |
F-stat | 361.34 | - | 344.19 | - | 344.24 | - | 328.64 | - |
Described Variables | NAEST | S.E | IF | S.E | AEST | S.E | IF | S.E |
---|---|---|---|---|---|---|---|---|
Fixed-Effects Models | Logit | Linear | Logit | Linear | ||||
Column (1) | Column (2) | Column (3) | Column (4) | |||||
Age | 0.359 | 0.228 | 0.001 | 0.083 | 0.004 | 0.236 | −0.001 | 0.083 |
Health status | 0.045 | 0.077 | 0.085 *** | 0.028 | −0.016 | 0.081 | 0.085 *** | 0.028 |
Education | −0.041 | 0.038 | 0.018 | 0.015 | −0.017 | 0.040 | 0.018 | 0.014 |
Household size | 0.104 *** | 0.0340 | −0.012 | 0.009 | −0.004 | 0.029 | −0.013 | 0.009 |
Land area | −0.261 *** | 0.030 | −0.261*** | 0.030 | −0.260 *** | 0.030 | −0.260 *** | 0.030 |
IT | 0.279 *** | 0.042 | 0.000 | 0.002 | −0.055 | 0.049 | 0.000 | 0.002 |
Income | 0.072 *** | 0.027 | 0.064 *** | 0.010 | −0.023 | 0.026 | 0.064 *** | 0.010 |
Asset | 0.009 | 0.016 | 0.087 *** | 0.007 | 0.035 * | 0.018 | 0.087 *** | 0.007 |
Cereal crop | 0.034 | 0.124 | 2.573 *** | 0.041 | 0.110 | 0.125 | 2.572 *** | 0.041 |
Mobile phone | 0.479 *** | 0.138 | −0.123 ** | 0.053 | −0.085 | −0.166 | 0.126 ** | 0.053 |
Agricultural Education | - | - | - | - | - | - | 0.210 *** | 0.063 |
Non-Agricultural Education | - | - | −0.117 ** | 0.055 | - | - | - | - |
Constant | - | - | 0.510 | 4.277 | - | - | 0.554 | 4.277 |
Individual effect | Yes | - | Yes | - | Yes | - | Yes | - |
Year effect | Yes | - | Yes | - | Yes | - | Yes | - |
Area dummies | Yes | - | Yes | - | Yes | - | Yes | - |
Observation numbers | 4957 | - | 31,036 | - | 3948 | - | 31,036 | - |
Group numbers | 1047 | - | 7514 | - | 833 | - | 7514 | - |
F-value | -- | - | 444.90 | - | -- | - | 335.45 | - |
Likelihood ratio test | 170.29 | - | -- | - | 42.64 | - | -- | - |
Described Variables: IF | Column (1) | S.E | Column (2) | S.E | Column (3) | S.E | Column (4) | S.E |
---|---|---|---|---|---|---|---|---|
Treat × T | −0.525 ** | 0.230 | −0.375 * | 0.217 | ||||
Treat × year2012 | - | - | - | −0.690 ** | 0.285 | −0.515 * | 0.270 | |
Treat × year2013 | - | - | - | - | −0.657 ** | 0.305 | −0.572 ** | 0.273 |
Treat × year2014 | - | - | - | - | −0.217 | 0.295 | −0.034 | 0.274 |
Treat | −0.281 | 0.170 | −0.666 *** | 0.162 | −0.278 | 0.170 | −0.065 *** | 0.170 |
Constant | 3.707 *** | 0.122 | −1.724 *** | 0.571 | 3.777 *** | 0.111 | −1.725 *** | 0.560 |
Year dummy | Yes | - | Yes | - | Yes | - | Yes | - |
Control variables | No | - | Yes | - | No | - | Yes | - |
Observation numbers | 6411 | - | 6411 | - | 6411 | - | 6411 | - |
F-value | 25.00 | - | 67.40 | - | 27.09 | - | 66.71 | - |
Result: IF | Unmatched (Matched) | Matched Mean | Percent Bias | Percent Reduce Bias | t-Test | ||
---|---|---|---|---|---|---|---|
Control | Treatment | t-Value | p-Value | ||||
Age | U (M) 1 | 37.20 (37.20) | 36.74 (35.38) | −19.0 (−2.4) | (87.6) | −6.05(−0.62) | 0.00 (0.53) |
Health status | U (M) | 4.59 (4.59) | 4.38 (4.58) | 43.8 (3.3) | (92.4) | 13.15 (0.88) | 0.00 (0.38) |
Education | U (M) | 7.99 (7.99) | 7.01 (6.93) | −5.8 (−2.0) | (65.1) | −1.83 (−0.53) | 0.07 (0.60) |
Household size | U (M) | 4.28 (4.28) | 4.64 (4.20) | −19.1 (4.6) | (75.7) | −6.50 (1.23) | 0.00 (0.214) |
Land area | U (M) | −0.32 (−0.32) | −0.24 (−0.41) | −9.4 (9.8) | (−4.4) | −2.75 (2.34) | 0.01 (0.02) |
Income | U (M) | 8.72 (8.72) | 8.67 (8.77) | 2.3 (−2.2) | (3.4) | 0.70 (−0.58) | 0.49 (0.56) |
Asset | U (M) | 6.30 (6.30) | 5.20 (6.25) | 31.4 (1.4) | (95.5) | 9.57 (0.40) | 0.00 (0.70) |
IT | U (M) | 1.73 (1.73) | 2.30 (2.59) | −5.0 (−7.6) | (−51.3) | −1.29 (−1.13) | 0.21 (0.25) |
Cereal crop | U (M) | 0.59 (0.59) | 0.53 (0.59) | 13.1 (1.4) | (89.5) | 5.13 (0.85) | 0.00 (0.88) |
Described Variables | Column (1) | S.E | Column (2) | S.E | Column (3) | S.E | Column (4) | S.E |
---|---|---|---|---|---|---|---|---|
Treat × T | −1.237 *** | 0.198 | −0.996 *** | 0.260 | ||||
Treat × year2012 | - | - | - | - | −1.233 *** | 0.370 | −1.068 *** | 0.345 |
Treat × year2013 | - | - | - | -- | −1.396 *** | 0.381 | −1.002 *** | 0.356 |
Treat × year2014 | - | - | - | - | −1.389 *** | 0.371 | −0.919 *** | 0.348 |
Treat | 0.139 | 0.217 | −0.110 | 0.203 | 0.139 | 0.217 | −0.110 | 0.203 |
Constant | 3.237 *** | 0.193 | 1.343 | 0.835 | 3.237 *** | 0.193 | 1.360 | 0.837 |
Year dummy | Yes | - | Yes | - | Yes | - | Yes | - |
Control variables | No | - | Yes | - | No | - | Yes | - |
Observation numbers | 2610 | - | 2610 | - | 2610 | - | 2610 | - |
F-value | 12.38 | - | 31.57 | - | 9.43 | - | 30.71 | - |
Described Variables | Column (1) | S.E | Column (2) | S.E |
---|---|---|---|---|
First-Stage | Two-Stage Least Squares | |||
Mobile Phone | IF | |||
IV | 0.727 *** | 0.446 | -- | -- |
Mobile phone | -- | -- | −0.543 *** | 0.187 |
Age | −0.002 | 0.010 | −0.002 | 0.083 |
Health status | 0.003 | 0.003 | 0.076 *** | 0.021 |
Education | −0.001 | 0.002 | 0.015 | 0.013 |
Household size | 0.004 *** | 0.001 | −0.014 | 0.008 |
Land area | −0.003 | 0.003 | −0.262 *** | 0.030 |
IT | 0.000 | 0.000 | 0.000 | 0.002 |
Income | 0.003 *** | 0.001 | 0.053 *** | 0.009 |
Asset | 0.001 *** | 0.001 | 0.089 *** | 0.006 |
Cereal crop | −0.001 | 0.005 | 2.662 *** | 0.032 |
Year effect | Yes | - | Yes | - |
Area dummies | Yes | - | Yes | - |
Individual effect | Yes | - | Yes | - |
Observation numbers | 15,223 | - | 15,223 | - |
First stage F statistic (P) | 444.90 | 0.000 | -- | - |
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Khan, N.; Ray, R.L.; Kassem, H.S.; Ihtisham, M.; Abdullah; Asongu, S.A.; Ansah, S.; Zhang, S. Toward Cleaner Production: Can Mobile Phone Technology Help Reduce Inorganic Fertilizer Application? Evidence Using a National Level Dataset. Land 2021, 10, 1023. https://doi.org/10.3390/land10101023
Khan N, Ray RL, Kassem HS, Ihtisham M, Abdullah, Asongu SA, Ansah S, Zhang S. Toward Cleaner Production: Can Mobile Phone Technology Help Reduce Inorganic Fertilizer Application? Evidence Using a National Level Dataset. Land. 2021; 10(10):1023. https://doi.org/10.3390/land10101023
Chicago/Turabian StyleKhan, Nawab, Ram L. Ray, Hazem S. Kassem, Muhammad Ihtisham, Abdullah, Simplice A. Asongu, Stephen Ansah, and Shemei Zhang. 2021. "Toward Cleaner Production: Can Mobile Phone Technology Help Reduce Inorganic Fertilizer Application? Evidence Using a National Level Dataset" Land 10, no. 10: 1023. https://doi.org/10.3390/land10101023