Identification strategy

I use and extend the work of CHL (2013) to identify countries where substantive enforce-ment changes occurred irrespective of IFRS adoption in order to separate IFRS and en-forcement effects as best as possible. CHL (2013) construct a data set containing whether and when substantive enforcement changes occurred in 56 IFRS and non-IFRS adoption countries from 2001 to 2009. The extensive data set displays the staggered introduction or strengthening of enforcement institutions for a global sample and also contains a large control sample without changes in enforcement. The given variation in IFRS adoption as well as enforcement changes and a set of fixed effects help CHL (2013) to overcome many of the typical issues of IFRS and enforcement research. For instance, the clustering in calendar time of IFRS adoption and enforcement changes mostly being directly tied to IFRS adoption make it difficult to empirically isolate their effects. Moreover, the effects of IFRS adoption and substantive changes in enforcement could mutually reinforce each other.

I arrive at two different treatment groups to investigate. Treatment group (I) consists of all the countries in CHL’s (2013) data set that have substantive enforcement changes sev-eral years after IFRS adoption plus Austria, which implemented an enforcement mecha-nism in 2013, and thus is not included in CHL’s (2013) data set. This treatment group’s potential enforcement effects might be dependent on prior IFRS adoption. However, as

the enforcement changes occurred several years after and not bundled with IFRS adop-tion, IFRS and enforcement effects are expected to be separated for the most part. In order to take prior IFRS adoption out of the equation, I introduce Treatment group (II). This group consists of non-IFRS-adopting countries with substantive enforcement changes.

Each of these treatment groups needs to be compared to a different set of control coun-tries. Treatment group (I) is compared to Control group (I), which consists of IFRS-adopt-ing countries that did not have substantive enforcement changes within the time frame under investigation. Together, Treatment group (I) and Control group (I) form the IFRS sample. Treatment group (II) is compared to countries that did not adopt IFRS nor carry out substantive enforcement changes in the defined time frame (Control group (II)). Treat-ment group (II) and Control group (II) constitute the Non-IFRS sample.

I establish these control groups by matching potential countries from CHL’s (2013) se-lection based on the Kaufmann et al. (2009) index for regulatory quality measured as of 2003.³⁰ Table 4.1 displays the composition of Treatment groups (I) and (II) and the re-spective control groups. Based on the work of CHL (2013), I know the exact quarter in which the enforcement changes occurred. This allows me to include another level of var-iation into my analyses. This is the varvar-iation in the publication of the first annual report by firms in a given country under the new enforcement regime as depicted in Table 4.2.

30 Equal to CHL (2013), I use the 2003 values of the regulatory quality index because I regard a similar time frame as they do in their study.

Table 4.1: Composition of treatment and control groups

Panel A: IFRS countries with or without following enforcement changes

Treatment Group (I) Control Group (I)

Panel B: Non-IFRS countries with or without following enforcement changes

Treatment Group (II) Control Group (II)

This table displays the composition of the two country groups under investigation as well as the respective control groups. Treatment Group (I) in Panel A consists of countries that had enforcement changes several years after IFRS adoption. This group is compared to a control group of countries which adopted IFRS but had no substantive enforcement changes in the regarded timeframe. Treatment Group (II) includes countries with substantive enforcement changes but without IFRS adoption and is compared to a control group of countries with neither enforcement changes nor IFRS adoption in the regarded time frame (Panel B). Countries were matched based on the regulatory quality index developed by Kaufmann et al. (2009).

Table 4.2: Variation in first annual report after enforcement change respective calendar quarter of the enforcement change. Moreover, this table depicts the variation in the date of publication of the first annual report under the new enforcement regime for the firms in the respective countries.

When carrying out my analyses, I regard the last two years prior to substantive ment changes and the first two years in the presence of a new or a strengthened enforce-ment regime. If I chose a longer time frame, I would face problems of overlapping with the date of IFRS adoption in Treatment group (I). For the control countries, I regard the same years as for the matched counterparts. My yearly panel regression model estimating the association between Enforcement and Conservatism looks as follows:

(1) 𝐶𝑜𝑛𝑠𝑒𝑟𝑣𝑎𝑡𝑖𝑠𝑚_𝑖𝑡 = 𝛽₁+ 𝛽₂𝐸𝑛𝑓𝑜𝑟𝑐𝑒𝑚𝑒𝑛𝑡_𝑖𝑡+ 𝛽₂𝑃𝑜𝑠𝑡_𝑖𝑡 + ∑ 𝐶𝑜𝑛𝑡𝑟𝑜𝑙𝑠_𝑖𝑡+

∑ 𝐹𝑖𝑥𝑒𝑑 𝑒𝑓𝑓𝑒𝑐𝑡𝑠 + 𝑒_𝑖𝑡

In line with my first hypothesis, I expect a positive association between Enforcement and Conservatism. I expect to find this association for both the IFRS sample and the Non-IFRS sample. To test my second hypothesis, investigating whether the role substantive changes in enforcement play in shaping conservative accounting choices depends on a firm’s corporate governance strength, I carry out a sub-sample analysis based on Ag-garwal et al.’s (2011)³¹ data set on corporate governance ratings. This data set contains

31 Aggarwal et al. (2011) investigate whether institutional investors have an impact on corporate governance. They analyse firms’ portfolio holdings from 23 countries from 2003 to 2008 and find that international institutional ownership is positively associated with firm-level governance.

corporate governance ratings for firms from 23 countries from 2003 to 2008. Their gov-ernance measure 𝐺𝑂𝑉₄₁ is based on 41 individual governance-related firm attributes. In this analysis, I only look at the countries with substantive enforcement changes: Treat-ment groups (I) and (III), namely Sweden, Lithuania, Ireland, Hungary, Hong Kong, Tur-key, Luxembourg, Austria, Japan and Chile. As Lithuania, Hungary, TurTur-key, Luxem-bourg and Chile are not included in the Aggarwal et al. (2011) data set and the relevant years for Austria (enforcement change was in 2013) are missing in the mentioned data set, I carry out my analysis with the sub-sample of firms from Sweden, Ireland, Hong Kong and Japan. I estimate regression model (1) for this sample including the variable Governance and the interaction term Enforcement*Governance.