If this parameter restriction is accepted, then the short-run process  translation - If this parameter restriction is accepted, then the short-run process  Indonesian how to say

If this parameter restriction is ac

If this parameter restriction is accepted, then the short-run process of price adjustment described by the model is consistent with an equilibrium in which a unit increase in central price is passed on fully in local prices. Notice that acceptance of the short-run restrictions implies long-run market integration but that the reverse is not true. If the long-run market integration restriction is accepted, then more efficient estimates of the remaining parameters and more powerful statistical tests will be possible if the model is reestimated with long-run integration imposed. For example, under long-run integration, equation (4) can be written in the following equivalent form:

This is a member of the class of error correlation models discussed by Hendry and Richard, and Hendry, Pagan, and Sargan. By interpretation, changes in local prices are attributed to changes in central prices and past spatial price differentials; the latter variables allow for the possibility that the markets are not observed in an integrated equilibrium at a given point in time, and so there is feedback from prior disequilibria. (See Salmon for a control theoretic interpretation of error correction models).
There are a number of possible variations around these three main hypotheses, particularly to do with the nonprice influences on each local market. The existence of significant localized market characteristics also indicates that arbitrage is imperfect in eliminating price differentials. Thus, stronger integration conditions can be formulated by adding c = 0 to the above restrictions. I shall return to this point in discussing the results for Bangladesh.
One problem that may arise when applying the above approach is multicollinearity among the regressors of the unrestricted model given by equation (4). The inferential difficulties that can arise are well known; a high standard error on, for example, the coefficient for central market price may be due to its high correlation with lagged local prices rather than weak market integration. However, such collinearity is a poor reason for adopting a more restrictive model specification. The bias induced by omitting relevant variables is well known. Also, the removal of such variables from a model can actually worsen the precision in estimation of the remaining regressors even when the two sets of variables are highly (albeit imperfectly) correlated (Davidson et al. give an example). Rather than impose parameter restrictions to reduce collinearity, a better approach in this setting is to first test for long-run integration; since this restriction involves all of the price variables, a good deal of the collinearity danger is avoided (possible correlations with Xi remain). If long-run integration is accepted, then it should be imposed on the model with subsequent tests based on a restricted form such as equation (II), for which the collinearity problem is likely to be a good deal less severe. If long-run integration is rejected, then this avenue is best closed off and so one should apply extra caution in rejecting the short-run integration conditions.

Spatial Price Differentials in Bangladesh 1972-1975

In this section the general approach outlined above will be applied to monthly district-level data on rice prices (coarse quality) for Bangladesh in the post-independence period as monitored by the Bangladesh Directorate of Agricultural Marketing. A thirty-six-month series was used, from July 1972 to June 1975. This period was chosen for its unusual price turbulence; there were numerous localized scarcities (particularly during the famine year 1974) and disturbances to trade and communications (for a detailed economic history of the period see Ravallion and van de Walle). Certainly this should be a hard (but important) test of the market integration restrictions.
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If this parameter restriction is accepted, then the short-run process of price adjustment described by the model is consistent with an equilibrium in which a unit increase in central price is passed on fully in local prices. Notice that acceptance of the short-run restrictions implies long-run market integration but that the reverse is not true. If the long-run market integration restriction is accepted, then more efficient estimates of the remaining parameters and more powerful statistical tests will be possible if the model is reestimated with long-run integration imposed. For example, under long-run integration, equation (4) can be written in the following equivalent form:

This is a member of the class of error correlation models discussed by Hendry and Richard, and Hendry, Pagan, and Sargan. By interpretation, changes in local prices are attributed to changes in central prices and past spatial price differentials; the latter variables allow for the possibility that the markets are not observed in an integrated equilibrium at a given point in time, and so there is feedback from prior disequilibria. (See Salmon for a control theoretic interpretation of error correction models).
There are a number of possible variations around these three main hypotheses, particularly to do with the nonprice influences on each local market. The existence of significant localized market characteristics also indicates that arbitrage is imperfect in eliminating price differentials. Thus, stronger integration conditions can be formulated by adding c = 0 to the above restrictions. I shall return to this point in discussing the results for Bangladesh.
One problem that may arise when applying the above approach is multicollinearity among the regressors of the unrestricted model given by equation (4). The inferential difficulties that can arise are well known; a high standard error on, for example, the coefficient for central market price may be due to its high correlation with lagged local prices rather than weak market integration. However, such collinearity is a poor reason for adopting a more restrictive model specification. The bias induced by omitting relevant variables is well known. Also, the removal of such variables from a model can actually worsen the precision in estimation of the remaining regressors even when the two sets of variables are highly (albeit imperfectly) correlated (Davidson et al. give an example). Rather than impose parameter restrictions to reduce collinearity, a better approach in this setting is to first test for long-run integration; since this restriction involves all of the price variables, a good deal of the collinearity danger is avoided (possible correlations with Xi remain). If long-run integration is accepted, then it should be imposed on the model with subsequent tests based on a restricted form such as equation (II), for which the collinearity problem is likely to be a good deal less severe. If long-run integration is rejected, then this avenue is best closed off and so one should apply extra caution in rejecting the short-run integration conditions.

Spatial Price Differentials in Bangladesh 1972-1975

In this section the general approach outlined above will be applied to monthly district-level data on rice prices (coarse quality) for Bangladesh in the post-independence period as monitored by the Bangladesh Directorate of Agricultural Marketing. A thirty-six-month series was used, from July 1972 to June 1975. This period was chosen for its unusual price turbulence; there were numerous localized scarcities (particularly during the famine year 1974) and disturbances to trade and communications (for a detailed economic history of the period see Ravallion and van de Walle). Certainly this should be a hard (but important) test of the market integration restrictions.
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Jika pembatasan parameter ini diterima, maka proses jangka pendek penyesuaian harga dijelaskan oleh model konsisten dengan keseimbangan di mana unit peningkatan harga pusat diteruskan sepenuhnya harga lokal. Perhatikan bahwa penerimaan pembatasan jangka pendek menyiratkan integrasi pasar jangka panjang tetapi sebaliknya tidak benar. Jika pembatasan integrasi pasar jangka panjang diterima, maka perkiraan yang lebih efisien dari parameter yang tersisa dan uji statistik yang lebih kuat akan mungkin jika model reestimated dengan integrasi jangka panjang yang dikenakan. Sebagai contoh, di bawah integrasi jangka panjang, persamaan (4) dapat ditulis dalam bentuk ekuivalen sebagai berikut: Ini adalah anggota dari kelas model korelasi error dibahas oleh Hendry dan Richard, dan Hendry, Pagan, dan Sargan. Dengan interpretasi, perubahan harga lokal yang dikaitkan dengan perubahan harga pusat dan perbedaan harga spasial masa lalu; variabel kedua memungkinkan untuk kemungkinan bahwa pasar tidak diamati dalam keseimbangan yang terintegrasi pada suatu titik waktu tertentu, dan sehingga ada umpan balik dari disequilibria sebelumnya. (Lihat Salmon untuk kontrol interpretasi teoritis model koreksi kesalahan). Ada beberapa kemungkinan variasi sekitar tiga hipotesis utama ini, terutama berkaitan dengan pengaruh nonharga pada setiap pasar lokal. Adanya karakteristik pasar lokal yang signifikan juga menunjukkan bahwa arbitrase tidak sempurna dalam menghilangkan perbedaan harga. Dengan demikian, kondisi integrasi yang lebih kuat dapat dirumuskan dengan menambahkan c = 0 pada pembatasan di atas. Aku akan kembali ke titik ini dalam membahas hasil untuk Bangladesh. Salah satu masalah yang mungkin timbul ketika menerapkan pendekatan di atas adalah multikolinearitas antara regressors model terbatas yang diberikan oleh persamaan (4). Kesulitan inferensial yang dapat timbul sudah dikenal; kesalahan standar yang tinggi pada, misalnya, koefisien untuk harga pasar sentral mungkin karena korelasi yang tinggi dengan harga lokal tertinggal ketimbang integrasi pasar yang lemah. Namun, collinearity tersebut adalah alasan yang buruk untuk mengadopsi model spesifikasi yang lebih ketat. Bias diinduksi dengan menghilangkan variabel yang relevan terkenal. Juga, penghapusan variabel tersebut dari model yang benar-benar dapat memperburuk presisi dalam estimasi regressors tersisa bahkan ketika dua set variabel sangat (meskipun tidak sempurna) berkorelasi (Davidson et al. Memberikan contoh). Daripada memberlakukan pembatasan parameter untuk mengurangi collinearity, pendekatan yang lebih baik dalam pengaturan ini adalah untuk ujian pertama bagi integrasi jangka panjang; karena pembatasan ini melibatkan semua variabel harga, banyak dari bahaya collinearity dihindari (mungkin korelasi dengan Xi tetap). Jika integrasi jangka panjang diterima, maka harus dikenakan pada model dengan tes berikutnya berdasarkan bentuk terbatas seperti persamaan (II), yang masalah collinearity cenderung banyak kurang parah. Jika integrasi jangka panjang ditolak, maka jalan ini paling tertutup dan jadi salah satu harus menerapkan ekstra hati-hati dalam menolak kondisi integrasi jangka pendek. spasial Diferensial Harga di Bangladesh 1972-1975 Pada bagian ini pendekatan umum yang diuraikan di atas akan diterapkan data bulanan tingkat kabupaten pada harga beras (kualitas kasar) untuk Bangladesh pada periode pasca-kemerdekaan sebagai dipantau oleh Bangladesh Direktorat Pemasaran Pertanian. Serangkaian tiga puluh enam bulan digunakan, dari Juli 1972 hingga Juni 1975. Periode ini dipilih untuk turbulensi harga yang tidak biasa; ada banyak kelangkaan lokal (terutama selama tahun kelaparan 1974) dan gangguan perdagangan dan komunikasi (untuk sejarah ekonomi rinci periode lihat Ravallion dan van de Walle). Tentu saja ini harus menjadi ujian yang sulit (tapi penting) dari pembatasan integrasi pasar.








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