Heterogeneity when accounting standards are non-binding: Internal service charges in the Swiss cantons

Figures & data

Table 1. Sub-categories to record ISCs according to the Conférence Cantonale des Directeurs des Finances (1981).

39	49	Internal service charges/revenue	Description
390	490	Procurement of materials and merchandise	Consideration for the supply of goods, appliances, machinery, movable properties, office items of all kinds
391	491	Services provided	Consideration for internal service delivery
392	492	Farm lease, rents, user charges	Consideration for rent paid to third parties for properties, premises, car parks and tangible fixed assets, appliances, vehicles etc.
393	493	Administration and operation expenses	Consideration for administration and operation expenses related to properties, facilities and movable properties used collaboratively or in sub-letting.
394	494	Imputed interest and finance costs	Consideration for imputed interest on administrative and non-administrative assets
395	495	Plan and unplanned depreciation	Planned and unplanned depreciation of administrative assets if they are not charged directly to the units
398	498	Transfers	Accounting transactions between units without involving a service, for example transfer of an amount from a unit to the income statement of an earmarked fund and vice versa
399	499	Other internal service charges/revenue	Considerations to other units or consolidated entities that are not otherwise reported

Notes: Identifiers for charges are in the first column and those for revenues are in the second one. The third column gives the category’s title and the last column provides a more detailed description.

Table 2. Summary statistics of the regression dataset.

Variable	N	Mean	SD	Min.	Max.
ISC intensity	799	0.075	0.074	0.000	0.424
ISC per capita	970	350.384	386.621	0.000	22.411
Year	988	1998	10.972	1980	2017
Election year (dummy)	988	0.247	0.431	0	1
Right-leaning parliament	988	0.412	0.151	0.000	0.817
Right-leaning executive	988	0.440	0.204	0.000	1.000
Political leaning of finance minister	962	5.953	1.348	2.600	7.700
Population (thousands)	988	278.301	291.490	12.757	1,504.346
Accounting maturity	988	6.417	2.482	2.500	13.995
Depreciation (CHF per capita)	808	0.537	0.391	0.032	3.357
Interest payments (CHF per capita)	988	0.971	2.034	0.000	11.511
Government size	799	146.381	92.267	17.877	770.929

Notes: This table contains all the variables used in the empirical analysis. ISC intensity, government size, depreciation and interest payments are based on the cantons’ statements of financial performance. Financial Maturity of different canton-years is based on Soguel and Luta (2021). Political variables are taken from the Swiss statistical office.

Table 3. Average share of ISC recorded in each subcategory.

		Mean	Median	Min.	Max.	Proportion of cantons using the category
390	Procurement of materials and merchandise	03.9	00.0	0.0	62.7	83.3
391	Services provided	26.5	19.2	0.0	93.3	83.3
392	Lease, rents, user fees	09.5	03.7	0.0	46.7	62.5
393	Administrative and operating expenses	02.3	00.1	0.0	21.5	62.5
394	Theoretical interest and finance costs	02.2	00.0	0.0	26.5	58.3
395	Scheduled and unscheduled depreciation	03.5	00.0	0.0	57.7	58.3
398	Transfers	20.0	05.8	0.0	91.0	45.8
399	Other ISCs	32.1	15.6	0.0	100.0	33.3

Notes: For each canton and year we computed the relative share of ISC entries booked in each separate sub-category. This table displays the distribution of sub-category specific ISC shares across canton-years. We also computed the proportion of cantons using the specific sub-category. ISC use was retrieved from the general-purpose financial reports of the individual cantons.

Figure 1. Share of precise and imprecise transactions in each canton.

Note: Dark blue bars represent ‘precise’ ISC entries, meaning that they are rounded to the ten-thousandth or below, over the total number of ISC transactions. Information is taken from the general-purpose financial reports from each canton.

Figure 2. Number of ISC sub-categories used per canton.

Notes: Dark blue bars represent the use of subcategories 390 to 398 which are specific entries (see Table 1 for detailed information). Light blue bars exhibit the use of subcategory 399 which can be considered as a residual subcategory. Sub-categories are given by CFM (1982).

Figure 3 – ISC intensity per canton.

Notes: Intensity is computed by dividing the sum of ISCs by overall expenses. The intensity is the 2016–2018 cantonal level average. Information is taken from the general purpose financial reports for each canton. Cantons are ranked by level of intensity.

Table 4. Regression results.

	log ISC per capita		log ISC intensity
	(1)	(2)	(3)	(4)
Constant	6.239***		-1.340
	(0.8851)		(2.908)
Political variables
Right-leaning parliament	1.615**	2.877***	1.117	2.704***
	(0.7291)	(0.6670)	(0.8789)	(0.7670)
Right-leaning executive	0.8312	-0.3959	0.8279	-0.4613
	(0.8213)	(0.6828)	(0.7832)	(0.6824)
Political leaning finance minister	-0.0153	-0.0006	-0.0073	-0.0092
	(0.0948)	(0.0551)	(0.0748)	(0.0568)
Election year	0.0472**	-0.0132	0.0359	-0.0171
	(0.0190)	(0.0342)	(0.0216)	(0.0359)
Accounting practices variables
Accounting maturity	-0.0647	-0.1402	-0.1373	-0.1223
	(0.0806)	(0.1721)	(0.0839)	(0.1749)
log Depreciation	0.3320*	0.0543	0.1342	0.0776
	(0.1796)	(0.0965)	(0.1650)	(0.1056)
log Interests liabilities	0.0028	0.3317**	-0.0246	0.3170*
	(0.0996)	(0.1548)	(0.1310)	(0.1607)
Structural variables
log Population			-0.1386	-0.7612
			(0.2496)	(3.156)
log Government size	-0.2029	0.0150
	(0.2120)	(0.1554)
Canton fixed effect	No	Yes	No	Yes
Year fixed effect	No	Yes	No	Yes
Observations	738	738	738	738
R^2	0.10522	0.73833	0.09106	0.76193
Within R^2	–	0.13591	–	0.12120

Notes: The coefficients displayed in this table stem from the regression of ISCs per capita or intensity on the various variables of interest. ISC intensity, government size, depreciation and interest payments are based on the cantons’ statements of financial performance. Financial maturity of different canton-years is based on Soguel and Luta (2021). Political variables are taken from the Swiss statistical office. Standard errors shown in parenthesis are robust and clustered at the cantonal level. Significance corresponds to *p < 0.1;**p < 0.05; ***p < 0.01.

Soguel, N., & Luta, N. (2021). On the road towards IPSAS with a maturity model: A Swiss case study. International Journal of Public Sector Management, 1–23.

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CFM—Conference of Cantonal Finance Ministers/Conférence des directrices et directeurs cantonaux des finances. (1982). Manuel de comptabilité publique. Vol. 1-2, Verlag Paul Haupt, Bern.

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