# Integration with world markets

The hypothesis of the law of one price between Indian and world markets is clearly rejected both for retail and wholesale prices. However, results show that the pass‐through from international to domestic prices is highly significant, in retail in the range of 62‐64 percent, while in wholesale in the range of 10‐11 percent. The results are robust across alternative specifications allowing for different lag structures (Table 2 for retail, Table 3 for wholesale), and they are aligned with the findings reported earlier when focusing on transmission of large price changes. Interestingly, exchange rate changes are fully transmitted to domestic wholesale prices in the long run, while domestic prices seem to react more proportionally to exchange rates, with a pass‐through coefficient above 1.4. For the speed of adjustment, the pattern reverses: it is greater for wholesale (more than double, in the range of 22 to 24 percent) than for retail (in the range of 11 to 12 percent). Notice however, that the reported speed of adjustment coefficients are averages across products and cities/districts, masking some heterogeneity.

Table 2: Results of error correction model, for retail, Table 3: Results of error correction model, for all commodities, all cities wholesale, all commodities, all districts

|Retail|(1)|(2)|(3)|(4)|Wholesale|(1)|(2)|(3)|(4)|
|---|---|---|---|---|---|---|---|---|---|
|_Speed of Adj (Avg)_|‐0.11***|‐0.11***|‐0.11***|‐0.12***|_Speed_<br>_of_<br>_Adj_<br>_(Avg)_|‐0.240***|‐0.22***|‐0.22***|‐0.22***|
||(0.008)|(0.008)|(0.009)|(0.009)||(0.0095)|(0.0081)|(0.008)|(0.008)|
|_Log International_|||||_Log International_|||||
|_Price_|0.62***|0.63***|0.64***|0.63***|_Price_|0.105***|0.11***|0.11***|0.11***|
||(0.0217)|(0.0213)|(0.0210)|(0.0212)||(0.007)|(0.008)|(0.008)|(0.008)|
|_Log NER_|1.40***|1.41***|1.44***|1.51***|_Log NER_|1.004***|1.02***|1.02***|1.04***|
||(0.0414)|(0.0399)|(0.0382)|(0.0378)||(0.0104)|(0.0108)|(0.0105)|(0.0103)|
|_Constant_|‐0.43***|‐0.45***|‐0.48***|‐0.53***|_Constant_|‐0.282***|‐0.27***|‐0.27***|‐0.29***|
||(0.026)|(0.029)|(0.031)|(0.035)||(0.0115)|(0.0106)|(0.0106)|(0.0110)|
|_Observations_|14,846|14,703|14,560|14,417|_Observations_|28,952|28,644|28,636|28,028|

Source: Authors’ calculations Source: Authors’ calculations The speed with which food prices adjust after a world price shock varies substantially by product, less so by state. Table 4 shows the speed of adjustment for each of the four products considered in this part of the analysis, averaged across states. For example, while in Uttar Pradesh coconut oil prices may only adjust at a rate of 3 percent per period, in Maharashtra prices adjust 14 percent of the disequilibrium per period. The heterogeneity is more marked across products than across city/states. For bananas, the speed of adjustment is, on average, 19 percent, while for rice it is less than a third, at 5.8 percent.

Table 4: Speed of adjustment of domestic to world price shocks by commodity and state (retail)

|**_State_**|**_Bananas_**|**_Coconut Oil_**|**_Groundnut Oil_**|**_Rice_**|
|---|---|---|---|---|
|Andhra Pradesh|‐0.1779|‐0.1554|‐0.0442|‐0.0967|
|Bihar|‐0.2111|‐0.0343|‐0.0381|‐0.0353|
|Goa|‐0.1032|‐0.0795||‐0.0814|
|Gujarat||‐0.0683|‐0.0755|‐0.0274|
|Haryana|‐0.2244|‐0.0568|‐0.0642|‐0.0570|
|Himachal Pradesh|‐0.1136|||‐0.0310|
|Jammu And Kashmir|‐0.3419|||‐0.0600|
|Jharkhand|‐0.4279|||‐0.0284|
|Karnataka||‐0.0764|‐0.1561|‐0.2299|
|Kerala|‐0.3828|‐0.0956|‐0.0816|‐0.0546|
|Madhya Pradesh|‐0.1685|‐0.0845|‐0.0315|‐0.1023|

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