10 The specification in column 2 may still be susceptible to omitted variable bias due to district-year shocks that may simultaneously influence field wages and program expenditure. For example, local adverse weather events may adversely affect the agriculture sector (and agricultural wages) while resulting in higher than expected program spending due to increased demand for public works.<sup>12</sup> Such local stresses like conflicts or weather abnormalities may negatively impact wages and result in higher than expected expenditure. If true, the estimated wage elasticity in column 2 is still likely to suffer from a downward bias. I exploit the two programs’ fund allocation process to construct a variable _Utilization ratiod,t_ that captures unexpected increases or decreases in spending that may represent potentially endogenous expenditure fluctuations.

**Table 1.** Impact of Public Works on Agricultural Wages

|||SGRY +|NREGA||Only NREGA|
|---|---|---|---|---|---|
||(1)|(2)|(3)|(4)|(5)|
|_sinh_<sup>_−_1</sup>(_ed,t_)|-4.493<sup>_∗∗_</sup>|4.250<sup>_∗∗∗_</sup>|5.936<sup>_∗∗∗_</sup>|2.342<sup>_∗∗_</sup>|1.341|
||[-2.123]|[1.215]|[1.295]|[1.021]|[1.034]|
|District effects|No|Yes|Yes|Yes|Yes|
|Year effects|No|Yes|Yes|Yes|Yes|
|Oth. controls|No|No|Yes|Yes|Yes|
|Het. trends|No|No|No|Yes|Yes|
|Observations|1340|1340|1340|1340|1340|

_Source_ : Author’s analysis based on AWI data (for field wages) and program expenditure data for SGRY and NREGA from 2001 to 2010. Program expenditure data is from the Ministry of Rural Development, Government of India. _Note_ : All estimates are of the order 10<sup>_−_2</sup> . The unit of observation is a district-year. The dependent variable in all the regressions is the log of field wages. Columns 1-5 have _sinh_<sup>_−_1</sup> ( _ed,t_ ) as the key regressor. In columns 1-4, program expenditure is for SGRY (b/w 2001 and 2007) and NREGA (b/w 2006 and 2010). In column 5, only expenditure under NREGA is considered (all expenditure values under SGRY are substituted by zero). The Inverse Hyperbolic Sine (IHS) transformation of the expenditure variable sinh<sup>_−_1</sup> ( _ed,t_ ) has the same interpretation as _log_ ( _ed,t_ ). Other controls include _NREGAd,t_ , _Util. Ratiod,t_ , _Raini,t_ , state elections-year indicator, and density of scheduled caste and scheduled tribe population in a district. All regressions are weighted by district-level population. The standard errors reported in square brackets are clustered at the district level and are robust to heteroskedasticity. SGRY: Sampoorna Grameen Rozgar Yojana. NREGA: National Rural Employment Guarantee Act. _∗ ∗∗ ∗∗∗ p <_ 0 _._ 10 _, p <_ 0 _._ 05 _, p <_ 0 _._ 01 For both SGRY and NREGA, the central government releases program funds to the states. The states, in turn, distribute the funds at the district level. Since both programs are in principle demand-driven, actual expenditure (or program liabilities) at the district level can be higher or lower relative to the total funds made available in any given year. The central government fulfills any excess expenditure in the next cycle. Hence, financial accounts roll over from one financial year to the next. Since there is information on both fund availability and actual expenditure at the district-year level, I construct _Utilization ratiod,t_ = 100 _∗ Actual expenditured,t/Funds made availabled,t_ . Consistent with public workfares being demand-driven, if deviations in actual expenditure relative to fund availability represent demand shocks, then this may confound the impact of employment policy on wages as reported in column 2 of table 1. Specifically, if over-utilization (under-utilization) of funds reflects more (less) demand for work under public workfares when the private labor market is slack (tight), then the elasticity estimate in column 2, table 1 will be downward biased.

To address these concerns, I estimate _β_<sup>�</sup> after controlling for such _potentially endogenous_ observations by

> 12 For example, Dr`eze (1990) discusses the increased take-up of public employment by laborers under Maharashtra’s public workfare during the famine of 1970-1973.