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From Table VII, the results reveal that IPSAS disclosure levels in sub-Saharan African governments range from 30.5 to 85.5 percent with an overall mean level of compliance of 62.5 percent and a standard deviation of 0.156 during the period 2014-2017. With regard to explanatory variables, the mean score of SPMS is 4 with a median of 4 and a standard deviation of 0.547. The mean score of the variable “ACCEDUC” is 0.730 with a median of 1 and a standard deviation of 0.445. The results of the correlation matrix and the VIF test are shown in Table VIII.

Table 8 From Table VII, the results reveal that IPSAS disclosure levels in sub-Saharan African governments range from 30.5 to 85.5 percent with an overall mean level of compliance of 62.5 percent and a standard deviation of 0.156 during the period 2014-2017. With regard to explanatory variables, the mean score of SPMS is 4 with a median of 4 and a standard deviation of 0.547. The mean score of the variable “ACCEDUC” is 0.730 with a median of 1 and a standard deviation of 0.445. The results of the correlation matrix and the VIF test are shown in Table VIII.

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4.2 Dependent variable 4.4 VEpenuent UUllaule In accordance with IPSAS texts and based on Ernst and Young (2012b) disclosure checklist, this study develops a self-constructed compliance checklist devoted to the measurement of IPSAS disclosure level. This checklist consists of 116 disclosure items related to the following accrual basis standards: IPSAS 1 “Presentation of financial statements,” IPSAS 2 “Cash flow statements,” IPSAS 3 “Accounting policies, changes in accounting estimates and errors,” IPSAS 14 “Events after the reporting date,” and IPSAS 24 “Presentation of budget information in financial statement.” These standards are selected as they contain the general and basic disclosures required to be provided in all government financial statements prepared under accrual-based accounting. Moreover, taking into account the differences in adoption status (full/partial) across countries, the research checklist mainly includes the minimum information[4] needed to be disclosed in accordance with IPSAS by all public sector entities (other than GBEs) as recommended by the IFAC. The study disclosure index was carefully prepared in order to minimize errors by removing some items whose applicability for a given entity cannot be judged by an outside review (Glaum et al, 2013). Therefore, the research instrument is adjusted for non-applicable items to avoid penalizing certain entities for not applying some irrelevant items (e.g. items related to accounting policies on financial instruments that the entity does not have, or on discontinued operations when the organization did not have any discontinued operations in either the current or the comparative period). The reliability of the checklist’s content[5] as reported in Table II] was checked by an independent IPSAS expert. +. ALTO Pe me seca ae 1 7 4 Pr rr er +1. sae
4.2 Dependent variable 4.4 VEpenuent UUllaule In accordance with IPSAS texts and based on Ernst and Young (2012b) disclosure checklist, this study develops a self-constructed compliance checklist devoted to the measurement of IPSAS disclosure level. This checklist consists of 116 disclosure items related to the following accrual basis standards: IPSAS 1 “Presentation of financial statements,” IPSAS 2 “Cash flow statements,” IPSAS 3 “Accounting policies, changes in accounting estimates and errors,” IPSAS 14 “Events after the reporting date,” and IPSAS 24 “Presentation of budget information in financial statement.” These standards are selected as they contain the general and basic disclosures required to be provided in all government financial statements prepared under accrual-based accounting. Moreover, taking into account the differences in adoption status (full/partial) across countries, the research checklist mainly includes the minimum information[4] needed to be disclosed in accordance with IPSAS by all public sector entities (other than GBEs) as recommended by the IFAC. The study disclosure index was carefully prepared in order to minimize errors by removing some items whose applicability for a given entity cannot be judged by an outside review (Glaum et al, 2013). Therefore, the research instrument is adjusted for non-applicable items to avoid penalizing certain entities for not applying some irrelevant items (e.g. items related to accounting policies on financial instruments that the entity does not have, or on discontinued operations when the organization did not have any discontinued operations in either the current or the comparative period). The reliability of the checklist’s content[5] as reported in Table II] was checked by an independent IPSAS expert. +. ALTO Pe me seca ae 1 7 4 Pr rr er +1. sae
index where each item is scored as disclosed (1), not disclosed (0) or not applicable (NA). An overall compliance index (IPSASDISCj#) is computed for each standard and for each government entity separately. In line with prior research (Mazzi et al, 2018; Glaum et al, 2013), IPSASDISC/t is the ratio of the total number (7) of items (dz) provided by the entity () to the maximum number of applicable items (//) for that entity during the year (f):
index where each item is scored as disclosed (1), not disclosed (0) or not applicable (NA). An overall compliance index (IPSASDISCj#) is computed for each standard and for each government entity separately. In line with prior research (Mazzi et al, 2018; Glaum et al, 2013), IPSASDISC/t is the ratio of the total number (7) of items (dz) provided by the entity () to the maximum number of applicable items (//) for that entity during the year (f):
regression models based on panel data: a main analysis model (Model 1) and a robustness analysis model (Model 2).
regression models based on panel data: a main analysis model (Model 1) and a robustness analysis model (Model 2).
CRIA es meen eens FEN EEE TE LORE E SOE S EAS Dah ASAT R TIM IER NATE ORE TS EE SERN TAN ORNR NTNATETE LIES | RRR A TA ETO NRL Meee Ainma® SHARE” | MNLORN LRM Sa In line with previous research ( and taking into consideration the disclosure levels. IPSASDISCRANI ranking entities (with the lowest compliance levels) and 1 corresponding to the highest ranking ones (with the highest com enhance the data structure by correcting for kurtosis and skewness whose test results in f the study model are normally distributed since the nul hypothesis of residual normality can be accepted at the 5 percent significance leve Table V reveal that the residuals o azzi et al, 2018; G K varies between 0 probability of non-normal distribution of the dependent variable, the IPSAS disclosure index IPSASDISC is transformed into percentile ranks. Based on this method, sampled entities are ranked in ascending order according to their IPSAS aum et al, 2013; Tsalavoutas, 2011 and 1, with 0 indicating the lowest pliance levels). This percentile rank method is relevant to
CRIA es meen eens FEN EEE TE LORE E SOE S EAS Dah ASAT R TIM IER NATE ORE TS EE SERN TAN ORNR NTNATETE LIES | RRR A TA ETO NRL Meee Ainma® SHARE” | MNLORN LRM Sa In line with previous research ( and taking into consideration the disclosure levels. IPSASDISCRANI ranking entities (with the lowest compliance levels) and 1 corresponding to the highest ranking ones (with the highest com enhance the data structure by correcting for kurtosis and skewness whose test results in f the study model are normally distributed since the nul hypothesis of residual normality can be accepted at the 5 percent significance leve Table V reveal that the residuals o azzi et al, 2018; G K varies between 0 probability of non-normal distribution of the dependent variable, the IPSAS disclosure index IPSASDISC is transformed into percentile ranks. Based on this method, sampled entities are ranked in ascending order according to their IPSAS aum et al, 2013; Tsalavoutas, 2011 and 1, with 0 indicating the lowest pliance levels). This percentile rank method is relevant to
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