80 Lampiran 2
Scripts Input dan Hasil Output Stata Estimasi Konvergensi dan Faktor-faktor yang Mempengaruhi Perubahan Harga Minyak
Goreng Di Indonesia dengan Model Panel Data Dinamis
Total 43.0104889
207 .20778014
Root MSE = .24324 Adj R-squared = 0.7152
Residual 11.9517632
202 .059167145
R-squared = 0.7221
Model 31.0587257
5 6.21174513
Prob F = 0.0000
F 5, 202 = 104.99
Source SS df MS Number of obs = 208
. reg hrg_minyak hrg_sebelum prod pdrb pendk jalan
delta: 1 unit time variable: tahun, 2002 to 2009
panel variable: prov strongly balanced
. tsset prov tahun . sort prov tahun
. egen prov = groupprovinsi
Prob chi2 = 0.2140
chi221 = 25.80345
H0: overidentifying restrictions are valid Sargan test of overidentifying restrictions
. estat sargan end of do-file
. H0: no autocorrelation
2 -3.7566 0.0002
1 -1.6806 0.0928
Order z Prob z Arellano-Bond test for zero autocorrelation in first-differenced errors
. estat abond
Standard: D.hrg_sebelum D.prod D.pdrb D.pendk D.jalan GMM-type: L2..hrg_minyak
Instruments for differenced equation errors are recommended.
Warning: gmm two-step standard errors are biased; robust standard
jalan .0709392 .0203793
3.48 0.000
.0309965 .1108819
pendk 8.422507 .4248788
19.82 0.000
7.58976 9.255254
pdrb .4249387 .0907402
4.68 0.000
.2470911 .6027862
prod .011149
.0016793 6.64
0.000 .0078576
.0144404 L1. .1048732
.0140404 7.47
0.000 .0773545
.1323918
hrg_minyak hrg_minyak Coef. Std. Err. z P|z| [95 Conf. Interval]
Two-step results
Prob chi2 = 0.0000
Number of instruments = 26
Wald chi25 = 26616.85
max =
6
avg = 6
Obs per group: min = 6
Time variable: tahun Group variable: prov Number of groups =
26
Arellano-Bond dynamic panel-data estimation Number of obs = 156
note: hrg_sebelum dropped because of collinearity . xtabond hrg_minyak hrg_sebelum prod pdrb pendk jalan, noconstant lags1 twostep artests2
81 Lampiran 3
Scripts Input dan Hasil Output Stata Estimasi Konvergensi dan Faktor-faktor yang Mempengaruhi Perubahan Harga Gula Pasir Di
Indonesia dengan Model Panel Data Dinamis
Total 16.854771
207 .081424014
Root MSE = .14211 Adj R-squared = 0.7520
Residual 4.07935445
202 .020194824
R-squared = 0.7580
Model 12.7754165
5 2.5550833
Prob F = 0.0000
F 5, 202 =
126.52
Source SS df MS Number of obs = 208
. reg hrg_gula hrg_sebelum prod pdrb pendk jalan
delta: 1 unit time variable: tahun, 2002 to 2009
panel variable: prov strongly balanced
. tsset prov tahun . sort prov tahun
. egen prov = groupprovinsi
Prob chi2 = 0.2201
chi221 = 25.64959
H0: overidentifying restrictions are valid Sargan test of overidentifying restrictions
. estat sargan end of do-file
. H0: no autocorrelation
2 -3.3454 0.0008
1 -4.0642 0.0000
Order z Prob z Arellano-Bond test for zero autocorrelation in first-differenced errors
. estat abond
Standard: D.hrg_sebelum D.prod D.pdrb D.pendk D.jalan GMM-type: L2..hrg_gula
Instruments for differenced equation errors are recommended.
Warning: gmm two-step standard errors are biased; robust standard
jalan .0178888 .0342073
0.52 0.601
-.0491562 .0849338
pendk 8.893077 .213438
41.67 0.000
8.474747 9.311408
pdrb .2259303 .0482968
4.68 0.000
.1312703 .3205902
prod .1096526 .030896
3.55 0.000
.0490976 .1702076
L1. -.2011949 .0121269
-16.59 0.000
-.2249633 -.1774265
hrg_gula hrg_gula Coef. Std. Err. z P|z| [95 Conf. Interval]
Two-step results
Prob chi2 = 0.0000
Number of instruments = 26
Wald chi25 = 412329.44
max = 6
avg = 6
Obs per group: min = 6
Time variable: tahun Group variable: prov Number of groups =
26
Arellano-Bond dynamic panel-data estimation Number of obs = 156
note: hrg_sebelum dropped because of collinearity . xtabond hrg_gula hrg_sebelum prod pdrb pendk jalan, noconstant lags1 twostep artests2
82 Lampiran 4
Scripts Input dan Hasil Output Stata Estimasi Konvergensi dan Faktor-faktor yang Mempengaruhi Perubahan Harga Kacang
Kedelai antar Wilayah di Indonesia dengan Model Panel Data Dinamis
Total 57.1721273
207 .276193852
Root MSE = .26895 Adj R-squared = 0.7381
Residual 14.6110125
202 .072331745
R-squared = 0.7444
Model 42.5611148
5 8.51222295
Prob F = 0.0000
F 5, 202 = 117.68
Source SS df MS Number of obs = 208
. reg hrg_kedelai hrg_sebelum prod pdrb pendk jalan
delta: 1 unit time variable: tahun, 2002 to 2009
panel variable: prov strongly balanced
. tsset prov tahun . sort prov tahun
. egen prov = groupprovinsi
. Prob chi2 =
0.2919 chi221 =
24.02481
H0: overidentifying restrictions are valid Sargan test of overidentifying restrictions
. estat sargan end of do-file
. H0: no autocorrelation
2 -.76955 0.4416
1 -1.0462 0.2955
Order z Prob z Arellano-Bond test for zero autocorrelation in first-differenced errors
. estat abond
Standard: D.hrg_sebelum D.prod D.pdrb D.pendk D.jalan GMM-type: L2..hrg_kedelai
Instruments for differenced equation errors are recommended.
Warning: gmm two-step standard errors are biased; robust standard
jalan -.2274683 .0703532
-3.23 0.001
-.365358 -.0895787
pendk 3.389198 .5077554
6.67 0.000
2.394016 4.38438
pdrb 1.499584 .1305277
11.49 0.000
1.243755 1.755414
prod .1037189 .0213857
4.85 0.000
.0618037 .1456341
L1. .0795217 .0110167
7.22 0.000
.0579293 .1011141
hrg_kedelai hrg_kedelai Coef. Std. Err. z P|z| [95 Conf. Interval]
Two-step results
Prob chi2 = 0.0000
Number of instruments = 26
Wald chi25 = 7170.40
max = 6
avg = 6
Obs per group: min = 6
Time variable: tahun Group variable: prov Number of groups =
26
Arellano-Bond dynamic panel-data estimation Number of obs =
156
note: hrg_sebelum dropped because of collinearity . xtabond hrg_kedelai hrg_sebelum prod pdrb pendk jalan, noconstant lags1 twostep artests2
83 Lampiran 5
Scripts Input dan Hasil Output Stata Estimasi Konvergensi dan Faktor-faktor yang Mempengaruhi Perubahan Harga Bawang
Merah Di Indonesia dengan Model Panel Data Dinamis
Total 27.4137402
207 .132433528
Root MSE = .20584 Adj R-squared = 0.6801
Residual
8.55916363 202
.042372097 R-squared = 0.6878
Model 18.8545766
5 3.77091532
Prob F = 0.0000
F 5, 202 = 89.00
Source SS df MS Number of obs = 208
. reg hrg_bawang hrg_sebelum prod pdrb pendk jalan
delta: 1 unit time variable: tahun, 2002 to 2009
panel variable: prov strongly balanced
. tsset prov tahun . sort prov tahun
. egen prov = groupprovinsi
Prob chi2 = 0.2378
chi221 = 25.21865
H0: overidentifying restrictions are valid Sargan test of overidentifying restrictions
. estat sargan end of do-file
. H0: no autocorrelation
2 1.8285
0.0675 1 -2.6945
0.0070
Order z Prob z Arellano-Bond test for zero autocorrelation in first-differenced errors
. estat abond
Standard: D.hrg_sebelum D.prod D.pdrb D.pendk D.jalan GMM-type: L2..hrg_bawang
Instruments for differenced equation errors are recommended.
Warning: gmm two-step standard errors are biased; robust standard
jalan .1291007 .0292405
4.42 0.000
.0717904 .186411
pendk 12.32787 .3338978
36.92 0.000
11.67344 12.98229
pdrb .6476677 .0610449
10.61 0.000
.5280219 .7673135
prod -.0007693 .0063254
-0.12 0.903
-.0131669 .0116284
L1. -.4310784 .0164947
-26.13 0.000
-.4634074 -.3987494
hrg_bawang hrg_bawang Coef. Std. Err. z P|z| [95 Conf. Interval]
Two-step results
Prob chi2 = 0.0000
Number of instruments = 26
Wald chi25 = 16160.13
max = 6
avg = 6
Obs per group: min = 6
Time variable: tahun Group variable: prov Number of groups =
26
Arellano-Bond dynamic panel-data estimation Number of obs = 156
note: hrg_sebelum dropped because of collinearity . xtabond hrg_bawang hrg_sebelum prod pdrb pendk jalan, noconstant lags1 twostep artests2
84 Lampiran 6
Scripts Input dan Hasil Output Stata Estimasi Konvergensi dan Faktor-faktor yang Mempengaruhi Perubahan Harga Cabe Merah
Di Indonesia dengan Model Panel Data Dinamis
Total 42.3591493
207 .204633572
Root MSE = .36212 Adj R-squared = 0.3592
Residual 26.4891014
202 .131134165
R-squared = 0.3747
Model 15.8700479
5 3.17400958
Prob F = 0.0000
F 5, 202 = 24.20
Source SS df MS Number of obs = 208
. reg hrg_cabe hrg_sebelum prod pdrb pendk jalan
delta: 1 unit time variable: tahun, 2002 to 2009
panel variable: prov strongly balanced
. tsset prov tahun . sort prov tahun
. egen prov = groupprovinsi
Prob chi2 = 0.2104
chi221 = 25.89835
H0: overidentifying restrictions are valid Sargan test of overidentifying restrictions
. estat sargan end of do-file
. H0: no autocorrelation
2 -4.0907 0.0000
1 -1.4155 0.1569
Order z Prob z Arellano-Bond test for zero autocorrelation in first-differenced errors
. estat abond
Standard: D.hrg_sebelum D.prod D.pdrb D.pendk D.jalan GMM-type: L2..hrg_cabe
Instruments for differenced equation errors are recommended.
Warning: gmm two-step standard errors are biased; robust standard
jalan -.1711598 .0595861
-2.87 0.004
-.2879463 -.0543732
pendk 12.44324 .532742
23.36 0.000
11.39908 13.48739
pdrb .451799
.0675274 6.69
0.000 .3194477
.5841504 prod -.0651503
.0055368 -11.77
0.000 -.0760023
-.0542984 L1. -.4877648
.0099501 -49.02
0.000 -.5072667
-.4682629
hrg_cabe hrg_cabe Coef. Std. Err. z P|z| [95 Conf. Interval]
Two-step results
Prob chi2 = 0.0000
Number of instruments = 26
Wald chi25 = 46000.30
max = 6
avg = 6
Obs per group: min = 6
Time variable: tahun Group variable: prov Number of groups =
26
Arellano-Bond dynamic panel-data estimation Number of obs = 156
note: hrg_sebelum dropped because of collinearity . xtabond hrg_cabe hrg_sebelum prod pdrb pendk jalan, noconstant lags1 twostep artests2
85 Lampiran 7
Scripts Input dan Hasil Output Stata Estimasi Konvergensi dan Faktor-faktor yang Mempengaruhi
Perubahan Harga Daging Ayam Di Indonesia dengan Model Panel Data Dinamis
Total 14.1276954
207 .068249736
Root MSE = .12642 Adj R-squared = 0.7658
Residual 3.22846512
202 .015982501
R-squared = 0.7715
Model 10.8992303
5 2.17984606
Prob F = 0.0000
F 5, 202 = 136.39
Source SS df MS Number of obs = 208
. reg hrg_ayam hrg_sebelum prod pdrb pendk jalan
delta: 1 unit time variable: tahun, 2002 to 2009
panel variable: prov strongly balanced
. tsset prov tahun . sort prov tahun
. egen prov = groupprovinsi
Prob chi2 = 0.2263
chi221 = 25.49644
H0: overidentifying restrictions are valid Sargan test of overidentifying restrictions
. estat sargan end of do-file
. H0: no autocorrelation
2 -.41378 0.6790
1 -2.7543 0.0059
Order z Prob z Arellano-Bond test for zero autocorrelation in first-differenced errors
. estat abond
Standard: D.hrg_sebelum D.prod D.pdrb D.pendk D.jalan GMM-type: L2..hrg_ayam
Instruments for differenced equation errors are recommended.
Warning: gmm two-step standard errors are biased; robust standard
jalan .0059907 .007987
0.75 0.453
-.0096635 .0216449
pendk 3.903322 .1659385
23.52 0.000
3.578089 4.228556
pdrb .6951284 .039542
17.58 0.000
.6176274 .7726294
prod .0501372 .0042041
11.93 0.000
.0418973 .0583771
L1. .1602223 .0157338
10.18 0.000
.1293845 .19106
hrg_ayam hrg_ayam Coef. Std. Err. z P|z| [95 Conf. Interval]
Two-step results
Prob chi2 = 0.0000
Number of instruments = 26
Wald chi25 = 24315.27
max = 6
avg =
6
Obs per group: min = 6
Time variable: tahun Group variable: prov Number of groups =
26
Arellano-Bond dynamic panel-data estimation Number of obs =
156
note: hrg_sebelum dropped because of collinearity . xtabond hrg_ayam hrg_sebelum prod pdrb pendk jalan, noconstant lags1 twostep artests2
86 Lampiran 8
Scripts Input dan Hasil Output Stata Estimasi Konvergensi dan Faktor-faktor yang Mempengaruhi Perubahan HargaTelur Ayam
Ras Di Indonesia dengan Model Panel Data Dinamis
Total 16.9799329
207 .082028661
Root MSE = .12357 Adj R-squared = 0.8138
Residual 3.08452354
202 .015269918
R-squared = 0.8183
Model 13.8954093
5 2.77908186
Prob F = 0.0000
F 5, 202 = 182.00
Source SS df MS Number of obs = 208
. reg hrg_telur hrg_sebelum prod pdrb pendk jalan
delta: 1 unit time variable: tahun, 2002 to 2009
panel variable: prov strongly balanced
. tsset prov tahun . sort prov tahun
. egen prov = groupprovinsi
. Prob chi2 =
0.2095 chi221 =
25.92063
H0: overidentifying restrictions are valid Sargan test of overidentifying restrictions
. estat sargan end of do-file
. H0: no autocorrelation
2 -2.2481 0.0246
1 -3.0857 0.0020
Order z Prob z Arellano-Bond test for zero autocorrelation in first-differenced errors
. estat abond
Standard: D.hrg_sebelum D.prod D.pdrb D.pendk D.jalan GMM-type: L2..hrg_telur
Instruments for differenced equation errors are recommended.
Warning: gmm two-step standard errors are biased; robust standard
jalan -.0550175 .0111543
-4.93 0.000
-.0768796 -.0331554
pendk 4.09919
.2324847 17.63
0.000 3.643528
4.554852 pdrb .7111886
.0657747 10.81
0.000 .5822725
.8401047 prod .0094962
.0023474 4.05
0.000 .0048954
.0140971 L1. .2632247
.0057601 45.70
0.000 .2519352
.2745143
hrg_telur hrg_telur Coef. Std. Err. z P|z| [95 Conf. Interval]
Two-step results
Prob chi2 = 0.0000
Number of instruments = 26
Wald chi25 = 177296.67
max = 6
avg = 6
Obs per group: min = 6
Time variable: tahun Group variable: prov Number of groups =
26
Arellano-Bond dynamic panel-data estimation Number of obs = 156
note: hrg_sebelum dropped because of collinearity . xtabond hrg_telur hrg_sebelum prod pdrb pendk jalan, noconstant lags1 twostep artests2
87 Lampiran 9
Scripts Input dan Hasil Output Stata Estimasi Konvergensi dan Faktor-faktor yang Mempengaruhi Perubahan Harga Daging Sapi
Di Indonesia dengan Model Panel Data Dinamis
Total 13.6229047
207 .065811134
Root MSE = .07227 Adj R-squared = 0.9206
Residual 1.05500761
202 .00522281
R-squared = 0.9226
Model 12.5678971
5 2.51357942
Prob F = 0.0000
F 5, 202 = 481.27
Source SS df MS Number of obs = 208
. reg hrg_dag_sapi hrg_sebelum prod pdrb pendk jalan
delta: 1 unit time variable: tahun, 2002 to 2009
panel variable: prov strongly balanced
. tsset prov tahun . sort prov tahun
. egen prov = groupprovinsi
Prob chi2 = 0.3074
chi221 = 23.70827
H0: overidentifying restrictions are valid Sargan test of overidentifying restrictions
. estat sargan end of do-file
. H0: no autocorrelation
2 .01359
0.9892 1 -3.0333
0.0024
Order z Prob z Arellano-Bond test for zero autocorrelation in first-differenced errors
. estat abond
Standard: D.hrg_sebelum D.prod D.pdrb D.pendk D.jalan GMM-type: L2..hrg_dag_sapi
Instruments for differenced equation errors are recommended.
Warning: gmm two-step standard errors are biased; robust standard
jalan .0090123 .0105729
0.85 0.394
-.0117102 .0297348
pendk 3.363051 .1571025
21.41 0.000
3.055135 3.670966
pdrb .3856356 .0309329
12.47 0.000
.3250082 .4462631
prod .0427545 .0034366
12.44 0.000
.0360188 .0494901
L1. .4106375 .01628
25.22 0.000
.3787293 .4425458
hrg_dag_sapi hrg_dag_sapi Coef. Std. Err. z P|z| [95 Conf. Interval]
Two-step results
Prob chi2 = 0.0000
Number of instruments = 26
Wald chi25 = 41942.58
max = 6
avg = 6
Obs per group: min =
6 Time variable: tahun
Group variable: prov Number of groups = 26
Arellano-Bond dynamic panel-data estimation Number of obs = 156
note: hrg_sebelum dropped because of collinearity . xtabond hrg_dag_sapi hrg_sebelum prod pdrb pendk jalan, noconstant lags1 twostep artests2
I. PENDAHULUAN
1.1 Latar Belakang
Pangan adalah kebutuhan pokok sekaligus menjadi esensi kehidupan manusia, dimana dalam Undang-undang nomor 7 tahun 1996 tentang Pangan
yang dirumuskannya sebagai usaha mewujudkan ketersediaan pangan bagi seluruh rumah tangga, dalam jumlah yang cukup, mutu dan gizi yang layak, aman
dikonsumsi, merata serta terjangkau oleh setiap individu. Kecukupan pangan menentukan kualitas sumber daya manusia dan ketahanan bangsa. Namun
kenyataannya Indonesia
belum mencapai
ketahanan pangan
karena ketergantungan terhadap pangan masih sangat tinggi, dimana dari pengeluaran
rata-rata rakyat Indonesia untuk makanan adalah masih cukup besar yaitu sebesar 50,62 persen pada tahun 2009 BPS 2009.
Produk Pangan pada umumnya mengikuti pola produksi musiman, sedangkan kebutuhan pangan harus dipenuhi sepanjang tahun. Selain itu produk
pertanian pada umumnya cepat rusak perishable. Dalam kondisi demikian maka aspek pengolahan dan penyimpanan menjadi hal penting dalam upaya penyediaan
pangan secara kontinyu. Di Indonesia, produksi pangan tersebar menurut agroekosistem dan geografinya, sedangkan lokasi konsumen tersebar di seluruh
pelosok tanah air, baik yang ditinggal di daerah perkotaan maupun pedesaan. Dengan demikian aspek transportasi dan distribusi pangan menjadi sangat vital
dalam rangka penyediaan pangan yang merata bagi seluruh penduduk Indonesia. Kurang meratanya penyediaan pangan bagi masyarakat menjadi memicu
kenaikan harga pangan. Fakta di lapangan menunjukkan bahwa sistem produksi dan sistem distribusi beberapa pangan terganggu karena kualitas sarana dan
prasarana transportasi banyak rusak. Beberapa media nasional dan daerah melaporkan rusaknya jalan di beberapa ruas di Pantai Utara Jawa, buruknya jalan
Lintas Tengah dan Lintas Timur di Sumatera, sebagai dua poros utama jalur distribusi pangan. Sementara aktivitas ekonomi di Pulau Jawa dan Sumatra
merupakan 84 persen penyumbang terhadap kinerja ekonomi nasional atau Produk Domestik Bruto PDB Indonesia. Betapa besar dan dahsyatnya apabila
sarana infrastruktur di Jawa dan Sumatera terganggu. Dampak buruk yang
