Table 2.
Multiple regression results: dependent variable = efficiency score
| Estimated coefficient (absolute value of t-statistic) | ||
|---|---|---|
| Ordinary least squares | Truncated regression model | |
| Constant | 0.6459*** (5.02) | 0.6678*** (15.05) |
| Fraction services produced by other agencies | −0.1706*** (3.77) | −0.1166** (2.37) |
| Fraction state and federal funding | −0.0004 (1.45) | −0.0004* (1.69) |
| Fraction White | 0.0011*** (2.68) | 0.0012*** (3.22) |
| Fraction Hispanic | 0.00004 (0.06) | 0.0006 (1.18) |
| County jurisdiction | −0.0525** (2.42) | −0.1117*** (5.87) |
| City/County jurisdiction | −0.0736*** (3.16) | −0.1178*** (5.49) |
| Regional jurisdiction | −0.0810*** (3.29) | −0.1335*** (5.79) |
| Other jurisdiction | −0.0692 (0.78) | −0.0620 (0.62) |
| Micropolitan area | 0.0712*** (5.87) | 0.0722*** (5.35) |
| Rural | 0.1201*** (9.95) | 0.1343*** (10.3) |
| Sigma | 0.1365** (35.0) | |
| Adjusted R2 | 0.334 | 0.416 |
| Log of likelihood function | 541.59 | 439.03 |
| Number of observations | 728 | 728 |
All models are specified with a set of 47 state dummy variables
***statistical significance at the 1% level
**statistical significance at the 5% level
*statistical significance at the 10% level