The Experts below are selected from a list of 3897 Experts worldwide ranked by ideXlab platform
Torluccio G. - One of the best experts on this subject based on the ideXlab platform.
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Does gender diversity on banks' boards matter? Evidence from public bailouts
2020Co-Authors: Cardillo G., Onali E., Torluccio G.Abstract:We are the first to examine the impact of gender diversity on banks' boards on the Probability and size of public bailouts. Our findings, based on a sample of listed European banks over the period 2005–2017, suggest that banks with more gender-diverse boards are less likely to receive a public bailout and receive a lower amount of bailout funds as a percentage of total assets than banks with less gender-diverse boards. Specifically, an increase by one standard deviation in gender diversity decreases the Probability of a bailout by at least 2.44%, a significant reduction considering that the Unconditional Probability is 18.7%. Gender diversity is also positively related to bank performance, as proxied by ROA and Tobin's Q and with dividend payout ratios, consistent with the hypothesis that female directors are better monitors than male directors. These results are robust to a variety of econometric approaches and provide support for recent reforms in several EU countries regarding gender quotas
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Does gender diversity on banks’ boards matter? Evidence from public bailouts
'Elsevier BV', 2020Co-Authors: Onali E., Cardillo G., Torluccio G.Abstract:This is the final version. Available on open access from Elsevier via the DOI in this recordWe are the first to examine the impact of gender diversity on banks’ boards on the Probability and size of public bailouts. Our findings, based on a sample of listed European banks over the period 2005-2017, suggest that banks with more gender-diverse boards are less likely to receive a public bailout and receive a lower amount of bailout funds as a percentage of total assets than banks with less gender-diverse boards. Specifically, an increase by one standard deviation in gender diversity decreases the Probability of a bailout by at least 2.44%, a significant reduction considering that the Unconditional Probability is 18.7%. Gender diversity is also positively related to bank performance, as proxied by ROA and Tobin’s Q and with dividend payout ratios, consistent with the hypothesis that female directors are better monitors than male directors. These results are robust to a variety of econometric approaches and provide support for recent reforms in several EU countries regarding gender quotas
John W Benoit - One of the best experts on this subject based on the ideXlab platform.
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Probability based models for estimation of wildfire risk
International Journal of Wildland Fire, 2004Co-Authors: Haiganoush K Preisler, David R Brillinger, Robert E Burgan, John W BenoitAbstract:We present a Probability-based model for estimating fire risk. Risk is defined using three probabilities: the Probability of fire occurrence; the conditional Probability of a large fire given ignition; and the Unconditional Probability of a large fire. The model is based on grouped data at the 1 km2-day cell level. We fit a spatially and temporally explicit non-parametric logistic regression to the grouped data. The Probability framework is particularly useful for assessing the utility of explanatory variables, such as fire weather and danger indices for predicting fire risk. The model may also be used to produce maps of predicted probabilities and to estimate the total number of expected fires, or large fires, in a given region and time period. As an example we use historic data from the State of Oregon to study the significance and the forms of relationships between some of the commonly used weather and danger variables on the probabilities of fire. We also produce maps of predicted probabilities for the State of Oregon. Graphs of monthly total numbers of fires are also produced for a small region in Oregon, as an example, and expected numbers are compared to actual numbers of fires for the period 1989–1996. The fits appear to be reasonable; however, the standard errors are large indicating the need for additional weather or topographic variables.
Cardillo G. - One of the best experts on this subject based on the ideXlab platform.
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Does gender diversity on banks' boards matter? Evidence from public bailouts
2020Co-Authors: Cardillo G., Onali E., Torluccio G.Abstract:We are the first to examine the impact of gender diversity on banks' boards on the Probability and size of public bailouts. Our findings, based on a sample of listed European banks over the period 2005–2017, suggest that banks with more gender-diverse boards are less likely to receive a public bailout and receive a lower amount of bailout funds as a percentage of total assets than banks with less gender-diverse boards. Specifically, an increase by one standard deviation in gender diversity decreases the Probability of a bailout by at least 2.44%, a significant reduction considering that the Unconditional Probability is 18.7%. Gender diversity is also positively related to bank performance, as proxied by ROA and Tobin's Q and with dividend payout ratios, consistent with the hypothesis that female directors are better monitors than male directors. These results are robust to a variety of econometric approaches and provide support for recent reforms in several EU countries regarding gender quotas
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Does gender diversity on banks’ boards matter? Evidence from public bailouts
'Elsevier BV', 2020Co-Authors: Onali E., Cardillo G., Torluccio G.Abstract:This is the final version. Available on open access from Elsevier via the DOI in this recordWe are the first to examine the impact of gender diversity on banks’ boards on the Probability and size of public bailouts. Our findings, based on a sample of listed European banks over the period 2005-2017, suggest that banks with more gender-diverse boards are less likely to receive a public bailout and receive a lower amount of bailout funds as a percentage of total assets than banks with less gender-diverse boards. Specifically, an increase by one standard deviation in gender diversity decreases the Probability of a bailout by at least 2.44%, a significant reduction considering that the Unconditional Probability is 18.7%. Gender diversity is also positively related to bank performance, as proxied by ROA and Tobin’s Q and with dividend payout ratios, consistent with the hypothesis that female directors are better monitors than male directors. These results are robust to a variety of econometric approaches and provide support for recent reforms in several EU countries regarding gender quotas
Onali E. - One of the best experts on this subject based on the ideXlab platform.
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Does gender diversity on banks' boards matter? Evidence from public bailouts
2020Co-Authors: Cardillo G., Onali E., Torluccio G.Abstract:We are the first to examine the impact of gender diversity on banks' boards on the Probability and size of public bailouts. Our findings, based on a sample of listed European banks over the period 2005–2017, suggest that banks with more gender-diverse boards are less likely to receive a public bailout and receive a lower amount of bailout funds as a percentage of total assets than banks with less gender-diverse boards. Specifically, an increase by one standard deviation in gender diversity decreases the Probability of a bailout by at least 2.44%, a significant reduction considering that the Unconditional Probability is 18.7%. Gender diversity is also positively related to bank performance, as proxied by ROA and Tobin's Q and with dividend payout ratios, consistent with the hypothesis that female directors are better monitors than male directors. These results are robust to a variety of econometric approaches and provide support for recent reforms in several EU countries regarding gender quotas
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Does gender diversity on banks’ boards matter? Evidence from public bailouts
'Elsevier BV', 2020Co-Authors: Onali E., Cardillo G., Torluccio G.Abstract:This is the final version. Available on open access from Elsevier via the DOI in this recordWe are the first to examine the impact of gender diversity on banks’ boards on the Probability and size of public bailouts. Our findings, based on a sample of listed European banks over the period 2005-2017, suggest that banks with more gender-diverse boards are less likely to receive a public bailout and receive a lower amount of bailout funds as a percentage of total assets than banks with less gender-diverse boards. Specifically, an increase by one standard deviation in gender diversity decreases the Probability of a bailout by at least 2.44%, a significant reduction considering that the Unconditional Probability is 18.7%. Gender diversity is also positively related to bank performance, as proxied by ROA and Tobin’s Q and with dividend payout ratios, consistent with the hypothesis that female directors are better monitors than male directors. These results are robust to a variety of econometric approaches and provide support for recent reforms in several EU countries regarding gender quotas
Haiganoush K Preisler - One of the best experts on this subject based on the ideXlab platform.
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Probability based models for estimation of wildfire risk
International Journal of Wildland Fire, 2004Co-Authors: Haiganoush K Preisler, David R Brillinger, Robert E Burgan, John W BenoitAbstract:We present a Probability-based model for estimating fire risk. Risk is defined using three probabilities: the Probability of fire occurrence; the conditional Probability of a large fire given ignition; and the Unconditional Probability of a large fire. The model is based on grouped data at the 1 km2-day cell level. We fit a spatially and temporally explicit non-parametric logistic regression to the grouped data. The Probability framework is particularly useful for assessing the utility of explanatory variables, such as fire weather and danger indices for predicting fire risk. The model may also be used to produce maps of predicted probabilities and to estimate the total number of expected fires, or large fires, in a given region and time period. As an example we use historic data from the State of Oregon to study the significance and the forms of relationships between some of the commonly used weather and danger variables on the probabilities of fire. We also produce maps of predicted probabilities for the State of Oregon. Graphs of monthly total numbers of fires are also produced for a small region in Oregon, as an example, and expected numbers are compared to actual numbers of fires for the period 1989–1996. The fits appear to be reasonable; however, the standard errors are large indicating the need for additional weather or topographic variables.
