rate for 1994-2003 as the cutoff point. The combined result is the four-quadrant grouping of states shown in Figure 1, with Gujarat, Haryana, Kerala, Maharashtra and Tamil Nadu as the high-income high-growth group of the first quadrant; Andra Pradesh, Karnataka, Rajasthan, and West Bengal as the low-income high-growth states of the second quadrant; Bihar, Madhya Pradesh, Orissa and Uttar Pradesh as the low-income lowgrowth states of the third quadrant; and Punjab as the sole high-income low-growth state of quadrant four. We take Delhi as a quadrant-one state but group Jharkhand along with the low-income low-growth states.<sup>2</sup> Quadrant-three states are what are sometimes referred to as ‘lagging regions’ in the policy literature in contrast to the ‘advanced states’ of quadrant one, with the ‘up-and-coming’ states of quadrant II in the middle. Our analysis will mainly focus on two- way comparisons of quadrant-three or low-income and low-growth states as base group with quadrant I and quadrant II states.

The enterprise performance indicators that we compute from the FACS survey data by state groups are consistent with the macroeconomic performance contrast implied by Figure 1. Thus average sales per worker is highest for enterprises from quadrant one states but lowest in quadrant- three states (Figure 2) which is consistent with quadrantone states being richer. Also, consistent with the income disparity between state groups, the gap in output per worker reflects the higher TFP levels of the average enterprise in quadrant-one states. Notice, however, that, although output per worker and productivity are higher in enterprises in higher income states, production is more capital intensive in lower income states. Moreover, wage rates are significantly higher in quadrant-two states than in quadrant-one states. Both suggest that the labor market might be most flexible in quadrant one states than in quadrant-two states- a suggestion that is born out by matching differences between the two states in terms of the ratings of labor regulation as a constraint to business growth by respondents to the FACS survey.

The patterns in business growth that we see in Figure 3a are also consistent with what we should expect given our state grouping criteria. Average business sales growth rates in low-income low-growth states were less than half of those of enterprises in high growth states. This pattern holds up when we measure growth in terms of fixed assets (Figure 3b) rather than sales. One major reason for the pattern is that gross fixed investment rates were consistently lowest in low-income low-growth states than in the higher growth states of both quadrant I and quadrant II (Figure 3c). A second reason into the details of which we will not go here is that enterprise productivity growth rates were also consistently and significantly lower in low-income low-growth states than in high-growth states (Honorati and Mengistae, 2007b).

These patterns seem to suggest that, over all, the policy and institutional environment of quadrant I and quadrant II states might be more conducive to business growth than that in quadrant III states, or ‘lagging regions’. We see from Table 1 that this is indeed the case in terms of the incidence of corruption as our proxy for the quality of property rights institutions, and our indicators of the state of power supply and indicators of two

> 2  The difference between the classification in Puriefied (2006) and ours here is that we are using more recent data, and consequently arrive at a slightly different grouping compared to hers.

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