Results 1 - 10 of 13,416

Table 12 Marginal effects on probability of hospital exit (for-profit and not-for-profit) For-profit exit Not-for-profit exit

in Does the Profit Motive Make Jack Nimble? Ownership Form and the Evolution of the U.S. Hospital Industry
by Sujoy Chakravarty, Martin Gaynor, William B. Vogt
"... In PAGE 17: ...Table12 for the marginal effects of county and hospital characteristics on the probability of exit for each group of hospitals. A comparison of coefficient estimates from the two logistic regressions reveals that lower growth of the elderly population increases the probability of exit for both for- profit and not-for-profit hospitals.... In PAGE 17: ... For both groups, the existence of a certificate of need law does not have a significant effect on the probability of exit. It is possible that the difference in for-profit and not-for-profit responsiveness reported in Table12 is due to differences in the distribution of characteristics among hospitals rather than the propensity to exit. To address this, we take the estimates from Table 12 and apply them out of sample to the dataset for the opposite ownership type.... In PAGE 17: ... It is possible that the difference in for-profit and not-for-profit responsiveness reported in Table 12 is due to differences in the distribution of characteristics among hospitals rather than the propensity to exit. To address this, we take the estimates from Table12 and apply them out of sample to the dataset for the opposite ownership type. The results of this exercise are reported in Table 13.... ..."

Table 3: Entry and exit of For-profit and Not-for-profit hospitals Entries Exits Incumbents

in Does the Profit Motive Make Jack Nimble? Ownership Form and the Evolution of the U.S. Hospital Industry
by Sujoy Chakravarty, Martin Gaynor, William B. Vogt
"... In PAGE 12: ... 2. Entry and Exit at the National and Regional Levels Table3 indicates that over the period 1984-2000, annual entry and exit rates were 1.... ..."

Table 14 : Comparing marginal Effects when public hospitals are also included For-profit (I) Not-for-profit (I) Public(I) For-profit (II) Not-for-profit (II) Public(II)

in Does the Profit Motive Make Jack Nimble? Ownership Form and the Evolution of the U.S. Hospital Industry
by Sujoy Chakravarty, Martin Gaynor, William B. Vogt

Table 3. Meta-Analyzed Empirical Papers on Marketing Orientation (MO)-Performance in the Not-for-Profit Sector

in unknown title
by unknown authors 2006
"... In PAGE 10: ... We now turn to the meta-analyzed papers. We identified 11 papers that assessed the MO-performance link in the VNPO context that included the information needed to summarize them quantitatively (see Table3 ). As our purpose is not to review the literature but to meta-analyze it, we briefly describe each paper.... ..."

Table: 8 Ordered Probit estimation of hospital entry in a county For-profit hospital Not-for-profit hospital

in Does the Profit Motive Make Jack Nimble? Ownership Form and the Evolution of the U.S. Hospital Industry
by Sujoy Chakravarty, Martin Gaynor, William B. Vogt

Table 15: Multinomial Logit: Marginal Effects on Probability of Hospital Exit Variable Public Not-for-profit For-profit

in Does the Profit Motive Make Jack Nimble? Ownership Form and the Evolution of the U.S. Hospital Industry
by Sujoy Chakravarty, Martin Gaynor, William B. Vogt
"... In PAGE 18: ... The conceptual model predicts that for-profits will have the highest exit rate and that the probability of the exit being for-profit (relative to the other two forms) will be decreasing in demand shifters. The coefficient estimates of the model are presented in Table15 . The probability that a given exiting hospital will be for-profit (in markets containing all three types) is over 70%.... ..."

Table 1 presents summary statistics for the different data sets used in the analysis. The top half of the table presents the summary statistics for the Medicare discharge data for the AMI and pneumonia diagnoses. The typical AMI patient is younger (75 versus 76.5 years), travels slightly further to her chosen hospital (7.7 versus 7.5 km), and is more likely to be admitted via the emergency room (63% versus 20%) than her pneumonia counterpart. Over a third of both AMI and pneumonia patients are admitted to the closest hospital. The hospital data is presented in the bottom half of Table 1. Both AMI and pneumonia carry a significant likelihood of death with the AMI mortality rate being higher than the pneumonia mortality rate (14.9% versus 9.5%). The relatively high likelihood of death for these conditions suggests that mortality is an appropriate measure of hospital quality. There is also significant variation in the mortality rates for both diagnoses across hospitals. The standard deviation is 3.9% and 2.3% for AMI and pneumonia, respectively. The average hospital has 242 staffed beds. The hospitals are roughly split between for-profit and not-for-profit hospitals (49% versus 44%) and 4% of the hospitals are members of the Council of Teaching Hospitals.

in and
by Gautam Gowrisankaran, Robert Town 2000

Table 1 presents summary statistics for the different data sets used in the analysis. The top half of the table presents the summary statistics for the Medicare discharge data for the AMI and pneumonia diagnoses. The typical AMI patient is younger (75 versus 76.5 years), travels slightly further to her chosen hospital (7.7 versus 7.5 km), and is more likely to be admitted via the emergency room (63% versus 20%) than her pneumonia counterpart. Over a third of both AMI and pneumonia patients are admitted to the closest hospital. The hospital data is presented in the bottom half of Table 1. Both AMI and pneumonia carry a significant likelihood of death with the AMI mortality rate being higher than the pneumonia mortality rate (14.9% versus 9.5%). The relatively high likelihood of death for these conditions suggests that mortality is an appropriate measure of hospital quality. There is also significant variation in the mortality rates for both diagnoses across hospitals. The standard deviation is 3.9% and 2.3% for AMI and pneumonia, respectively. The average hospital has 242 staffed beds. The hospitals are roughly split between for-profit and not-for-profit hospitals (49% versus 44%) and 4% of the hospitals are members of the Council of Teaching Hospitals.

in and
by Gautam Gowrisankaran, Robert Town 2000

Table 4: Respondent profile

in Multi-stakeholder Partnerships in Affordable Rental Housing: an Investigation Using Soft Systems Framework
by Lynne Multistakeholder
"... In PAGE 8: ... There were 17 people interviewed comprising, seven representatives of the private sector, five government officers and five representatives of not-for-profit organisations. Table4 describes the composition of each sub-group classified by the scope of their organisation and their gender. 1.... ..."

Table 5. Selected games and players shaping Internet governance

in The Emerging Internet Governance Mosaic: Connecting the Pieces
by William H. Dutton, Malcolm Peltu 2005
"... In PAGE 11: ... The US government was generally felt to have been even-handed to date in instigating the Internet and supporting its openness and independence principles. However, as indicated below in a discussion relating to Table5 in Section 3, there is a continuing political struggle over who controls and manages the root servers.6 The status of ICANN as a not-for-profit corporation was also the focus of some differences of opinion, discussed at the forum particularly in the context of the cybersquatting UDRP.... ..."
Cited by 1
Results 1 - 10 of 13,416