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New York August 1-5, 2009 S. Cascino AAA 2009 Annual Meeting New York August 1-5, 2009 Do harmonized accounting standards lead to harmonized accounting?

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Presentation on theme: "New York August 1-5, 2009 S. Cascino AAA 2009 Annual Meeting New York August 1-5, 2009 Do harmonized accounting standards lead to harmonized accounting?"— Presentation transcript:

1 New York August 1-5, 2009 S. Cascino AAA 2009 Annual Meeting New York August 1-5, 2009 Do harmonized accounting standards lead to harmonized accounting? German-Italian Evidence Stefano Cascino University of Naples Federico II Joachim Gassen Humboldt-Universität zu Berlin

2 1 Motivation Regulation (EC) No. 1606/2002, Art. 1 New York August 1-5, 2009 S. Cascino

3 Regulation (EC) No. 1606/2002, Art. 1 22 Motivation New York August 1-5, 2009 S. Cascino

4 Regulation (EC) No. 1606/2002, Art. 1 33 Motivation New York August 1-5, 2009 S. Cascino

5 Regulation (EC) No. 1606/2002, Art. 1 44 Motivation New York August 1-5, 2009 S. Cascino

6 Regulation (EC) No. 1606/2002, Art. 1 55 Motivation New York August 1-5, 2009 S. Cascino

7 Regulation (EC) No. 1606/2002, Art. 1 66 Motivation New York August 1-5, 2009 S. Cascino

8 Regulation (EC) No. 1606/2002, Art. 1 77 Motivation New York August 1-5, 2009 S. Cascino

9 88 The quasi-experimental setting: Infrastructure (some stats) StatisticGermanyItaly Market capitalization / GDP63%51% Turnover / Market capitalization205%216% % of market widely owned50%20% % of market family owned10%15% % of market state owned25%40% % of market owned by financial institutions15%10% Corruption Perception Index7.8 (17/179)5.2 (41/179) Legal Right Index8/105/10 Sources: See paper New York August 1-5, 2009 S. Cascino

10 99 Conceptual Research Question Does the adoption of IFRS lead to harmonized accounting information across Germany and Italy?...or do incentives prevail regardless of harmonized accounting standards? New York August 1-5, 2009 S. Cascino

11 10 Main Findings Traditional earnings attributes metrics are inappropriate and lack power for testing for economically significant differences in our setting Differences in intangible assets recognition between German and Italian firms mitigated by IFRS adoption Significant differences in IFRS measurement and even more disclosure compliance between German and Italian firms as well as between German late and early adopters persist These differences can be linked to firm-, region-, and country-level incentives New York August 1-5, 2009 S. Cascino

12 11 Some Recent Literature Beuselink/Joos/van der Meulen (WP, 2007): Investigate earnings comparability across EU from 1990-2005 using Ball/Shivakumar type accrual cash flow relation, show increasing trend over time Bradshaw/Miller (WP, 2007): Look at increased comparability of non-US firms cross- listing in the U.S. investigating accounting choices (as provided by Worldscope) and asymmetric timeliness as well as accrual/cash flow relations De Franco/Kothari/Verdi (WP, 2008): construct a firm-specific measure of accounting comparability using cross-industry earnings returns and earnings-other earnings relations estimated on firm-specific time series. Show that this metric is related to analyst forecast quality (precision, dispersion and bias) New York August 1-5, 2009 S. Cascino

13 12 Test Design Investigate earnings attributes across Germany and Italy pre and post IFRS adoption asymmetric timeliness earnings smoothness Study differences in intangible assets recognition across Germany and Italy pre and post IFRS adoption goodwill other intangible assets Study differences in 2006 IFRS compliance across Germany and Italy measurement disclosure Test for compliance determinants New York August 1-5, 2009 S. Cascino

14 13 Data Background Earnings attributes and levels of intangibles recognition are estimated for a sample of 3,730 Italian and German public firm years over the 1998 to 2006 time period Accounting data from Worldscope Capital market data from Datastream Propensity score matching used to match German on Italian firms Compliance data has been hand-collected from the 2006 annual reports 153 public Italian firms (full population) 135 German late adopters (full population) 117 German early adopters (matched on Italian firms) New York August 1-5, 2009 S. Cascino

15 14 The Problem of Earnings Attributes: Asymmetric Timeliness Full Sample Matched Sample Local GAAPIFRSLocal GAAPIFRS ParameterEstimatet ValueEstimatet ValueEstimatet ValueEstimatet Value Intercept0.0333.18***0.0263.26***0.0554.48***0.0453.15*** ITALY0.0010.09-0.003-0.22-0.021-1.38-0.023-1.16 NEG0.0090.78-0.010-0.77-0.007-0.54-0.011-0.47 ITALY*NEG-0.022-1.36-0.009-0.37-0.006-0.35-0.007-0.24 RETURN0.0201.000.0110.690.0180.78-0.029-0.85 ITALY*RETURN0.0150.530.0240.610.0170.580.0641.29 NEG*RETURN0.3249.24***0.2827.98***0.2315.23***0.2693.09*** ITALY*NEG*RETURN-0.109-2.15**-0.032-0.31-0.016-0.29-0.019-0.14 n3,0562,0302,004708 Adj. R²0.1760.1360.1750.135 New York August 1-5, 2009 S. Cascino

16 15 The Problem of Earnings Attributes: Earnings Smoothness 0 0.5 1 1.5 2 2.5 3 199819992000200120022003200420052006 GER GAAP GER IFRS ITA GAAP ITA IFRS SMOOTH: std(CFO)/std(NIBE) SMOOTH YEAR New York August 1-5, 2009 S. Cascino

17 16 Results: Intangibles Recognition local GAAP Germany Matched Sample (n=846) VariableMeanSD25 %50 %75 %t-valueZ-Score INTASS0.0810.1200.0060.0260.109-5.91***-9.03*** GOODWILL0.0400.0830.000 0.042-5.56***-10.16*** OTHER_INTASS0.0400.0870.0030.0080.030-2.82***-8.80*** Italy (n=906) VariableMeanSD25 %50 %75 % INTASS0.1170.1370.0190.0680.164 GOODWILL0.0640.0970.0000.0230.085 OTHER_INTASS0.0530.0960.0080.0190.052 New York August 1-5, 2009 S. Cascino

18 17 Results: Intangibles Recognition IFRS Germany Matched Sample (n=350) VariableMeanSD25 %50 %75 %t-valueZ-score INTASS0.1510.1580.0290.0970.231-0.270.07 GOODWILL0.0950.1220.0020.0420.1540.05-0.37 OTHER_INTASS0.0560.1070.0070.0180.053-0.490.45 Italy (n=354) VariableMeanSD25 %50 %75 % INTASS0.1550.1640.0250.0920.232 GOODWILL0.0940.1300.0060.0400.121 OTHER_INTASS0.0600.1000.0040.0180.076 New York August 1-5, 2009 S. Cascino

19 18 Results: Intangibles Recognition Multivariate Analysis ***/**/* marks two-sided significance for the interacted version of the model at the 1/5/10% level Pre IFRSPost IFRS ParameterSignEstimatePr > |t|EstimatePr > |t| LOG(MKTCAP)+0.0180.0000.0160.000 ROA+/--0.1140.007-0.0520.447 MTB+0.0000.9440.004***0.003 LEVERAGE+/-0.1020.0000.189**0.000 FREQ_LOSSES+0.0160.2250.0280.211 ITALY+/-0.0130.019-0.005*0.700 Industry fixed effectsYes Year fixed effectsYes n (R²) 1,758 (0.494)705 (0.570) New York August 1-5, 2009 S. Cascino

20 19 Results: 2006 IFRS Measurement Compliance Matched Sample Germany MatchedItaly StandardnMeanSDnMeanSDt-valueZ-score IFRS 2 511.0000.000 670.9250.265 2.01**1.98** IAS 11 291.0000.000 481.0000.000 -0.00 IAS 17 901.0000.000 1250.9920.089 0.850.84 IAS 19 1100.9910.095 1530.9670.178 1.26 IAS 36 1400.9790.118 1530.9640.153 0.900.92 IAS 38 1510.9500.161 1520.9740.138 -1.36-1.83* IAS 39 1210.9360.149 1320.9780.100 -2.61***-2.70*** New York August 1-5, 2009 S. Cascino

21 20 Results: 2006 IFRS Disclosure Compliance Matched Sample Germany MatchedItaly StandardnMeanSDnMeanSDt-valueZ-score IFRS 2570.6810.360660.8280.327-2.37**-2.66*** IAS 11290.8740.226490.6730.3572.71***2.62*** IAS 171370.8150.3081250.6130.3704.81***4.83*** IAS 191170.6860.2961530.6730.3200.760.51 IAS 331530.8870.2091530.8400.2731.71*0.76 IAS 361250.5170.4181520.4710.4030.930.81 IAS 381510.9290.1831530.7410.3326.13***5.60*** IAS 391220.6330.3511310.6910.384-1.26-1.73* New York August 1-5, 2009 S. Cascino

22 21 Results: Disclosure Compliance Determinants GermanyItaly (-***) ParameterSignEstimatePr > |t| EstimatePr > |t| LOG(TOTASS)+0.0270.0000.056**0.000 ROA+/- 0.0050.955 0.801**0.005 MTB+-0.0010.6010.008*0.127 FREQ_LOSSES+0.0530.1560.0900.115 INDEP_BOARD_D+0.0520.0100.0830.011 INSTOWN+/--0.0140.5440.0150.659 GOVOWN+/--0.0410.414-0.0550.350 FAMBUS--0.0340.2190.0070.859 BIG4+0.0470.0350.140*0.003 LD_REGION-0.0180.653-0.278***0.001 EARLY+0.1040.000 Industry fixed effectsYes n (R²) 252 (0.350) 153 (0.466) ***/**/* marks two-sided significance for the interacted version of the model at the 1/5/10% level New York August 1-5, 2009 S. Cascino

23 22 Some limitations Internal Validity Quasi-experimental setting: Treatments country and accounting regime are not random Propensity score matching does not fully address this concern Suitable proxies for comparability of accounting information Limited sample of IFRS firm-years Tests rely on models capturing economic reality Omitted variables? Endogeneity concerns? External Validity Private firms Other (non-European) countries? New York August 1-5, 2009 S. Cascino

24 23 Conclusions Stressing the importance of the limitations discussed above: Earnings attributes are too noisy to document the impact of accounting rule changes over short time horizons We are able to document increased comparability after IFRS adoption Nevertheless, differences in measurement and – more pronounced – disclosure compliance remain and can be linked to country-, region- and firm-level determinants Its the standards and the incentives, stupid! New York August 1-5, 2009 S. Cascino

25 24 AAA 2009 Annual Meeting New York August 1-5, 2009 stefano.cascino@unina.it Thanks for Your Attention! New York August 1-5, 2009 S. Cascino

26 25 Motivation… Part two Bushman/Piotroski, JAE 2006, p.145 New York August 1-5, 2009 S. Cascino

27 26 Bushman/Piotroski, JAE 2006, p.145 Motivation… Part two New York August 1-5, 2009 S. Cascino

28 27 Test design: Address self-selection Quasi-experimental design: The subjects are treated non-randomly - Decision to IFRS differs across Germany and Italy - Decision to go public differs across Germany and Italy Propensity score matching technique is applied to match Italian firms with German firms Separately for local GAAP and IFRS firms the following logit model is estimated New York August 1-5, 2009 S. Cascino

29 28 The quasi-experimental setting: IFRS adoption over time 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 199819992000200120022003200420052006 Germany Italy % of IFRS YEAR New York August 1-5, 2009 S. Cascino

30 29 Test design: Address self-selection Germany Full Sample Germany Matched SampleItaly Industry (first-digit SIC- Code)FrequencyPercentFrequencyPercentFrequencyPercent 0110.2980.5990.66 11123.00604.42463.39 262916.8627320.1326919.84 3130935.0948735.9145133.26 43178.5024317.9229821.98 547812.82795.83916.71 769818.7118413.5717913.20 81684.50161.18130.96 980.2160.4400.00 Total3,7301,356 New York August 1-5, 2009 S. Cascino

31 30 Results: Asymmetric Timeliness Full Sample Local GAAPIFRS ParameterEstimatet ValueEstimatet Value Intercept0.0333.18***0.0263.26*** ITALY0.0010.09-0.003-0.22 NEG0.0090.78-0.010-0.77 ITALY*NEG-0.022-1.36-0.009-0.37 RETURN0.0201.000.0110.69 ITALY*RETURN0.0150.530.0240.61 NEG*RETURN0.3249.24***0.2827.98*** ITALY*NEG*RETURN-0.109-2.15**-0.032-0.31 n3,0562,030 Adj. R²0.1760.136 New York August 1-5, 2009 S. Cascino

32 31 Results: Asymmetric Timeliness Matched Sample Local GAAPIFRS ParameterEstimatet ValueEstimatet Value Intercept0.0554.48***0.0453.15*** ITALY-0.021-1.38-0.023-1.16 NEG-0.007-0.54-0.011-0.47 ITALY*NEG-0.006-0.35-0.007-0.24 RETURN0.0180.78-0.029-0.85 ITALY*RETURN0.0170.580.0641.29 NEG*RETURN0.2315.23***0.2693.09*** ITALY*NEG*RETURN-0.016-0.29-0.019-0.14 n2,004708 Adj. R²0.1750.135 New York August 1-5, 2009 S. Cascino

33 32 Results: 2006 IFRS Measurement Compliance Late Adopters Germany LateItaly StandardnMeanSDnMeanSDt-valueZ-score IFRS 2151.0000.000670.9250.2651.091.07 IAS 11201.0000.000481.0000.000n/a IAS 17750.9870.1151250.9920.089-0.37-0.36 IAS 191110.9910.0951530.9670.1781.27 IAS 361200.9500.1761530.9640.153-0.70-0.78 IAS 381350.9300.1851520.9740.138-2.30**-2.81*** IAS 391070.8980.2171320.9780.100-3.77***-3.90*** New York August 1-5, 2009 S. Cascino

34 33 Results: 2006 IFRS Disclosure Compliance Late Adopters Germany LateItaly StandardnMeanSDnMeanSDt-valueZ-score IFRS 2170.5590.328660.8280.327-3.03***-3.23*** IAS 11210.8100.249490.6730.3571.591.38 IAS 171200.7720.3431250.6130.3703.48***3.67*** IAS 191210.6070.3181530.6730.320-1.27-1.49 IAS 331360.8270.2311530.8400.273-0.42-1.77* IAS 361050.3240.3341520.4710.403-3.09***-2.88*** IAS 381350.8770.2401530.7410.3323.93***3.58*** IAS 391070.4600.3051310.6910.384-5.06***-5.35*** New York August 1-5, 2009 S. Cascino


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