Capital market response to high quality annual reporting: evidence from UK annual report awards

Figures & data

Figure 1. Decision tree for categorising FTSE350 firm-year observations. Year t is the award year (2007–2019). This figure provides a framework for classifying firms into three categories based on (a) whether the firm was shortlisted for an award in year t and (b) whether it was shortlisted for an award in either the two previous years (t−2 or t−1) or the two subsequent years (t + 1 or t + 2). Category one (C1) consists of firms that was shortlisted in year t. Category two (C2) consists of firms that were not shortlisted in year t but shortlisted in the 5-year window t−2 to t + 2. Category three (C3) consists of firms that have not been shortlisted for an award in the period t−2 to t + 2.

Table 1. Sample size and classification.

	Total population	Award shortlisted observations	Non-award shortlisted observations
FTSE350 Constituent firm-years (2007–2019)	4,550	484	4,066
less: missing identifiers	(245)	(0)	(245)
less: trust or hedge fund firms (SIC 6726–6794 & 6799)	(510)	(0)	(510)
	3,795	484	3,311
less: limited data availability	(1,028)	(91)	(937)
Remaining Sample	2,767	393	2,374
less: non-award observations of award firms	(437)	(0)	(437)
Final Sample	2,330	393	1,937

This table shows the formation of the samples used as the basis for tests and regressions in the remainder of this paper from the population of FTSE350 constituents over the period 2007–2019. The total population of firms is segregated between firm-year observations that have (have not) been shortlisted for a U.K. annual reporting award the two previous years or the two subsequent years. The ‘remaining sample’ is used for descriptive statistics while the ‘final sample’ represents the sample used for multiple regression analysis upon which the PSM process is based.

Table 2. Firm awards over the sample period.

Number of years shortlisted for an award	Number of firms	Total award observations
1	51	51
2	24	48
3	16	48
4	14	56
5	12	60
6	9	54
7	1	7
8	2	16
9	1	9
10	2	20
11	1	11
12	0	0
13	1	13
Totals	134	393

This table shows the distribution of award shortlisted firms across the number of years in which they are shortlisted for a U.K. narrative reporting award. Total award observations is the product of the first two columns. For example, two firms are shortlisted for an award for ten years, resulting in a total of 20 shortlisted observations for these two firms.

Table 3. Duration of firms in the sample period (2007–2019).

Count of sample years	Award firms	Never-award firms	Total Number of firms
1	1	52	53
2	3	29	32
3	6	18	24
4	6	14	20
5	7	22	29
6	4	15	19
7	7	14	21
8	10	11	21
9	11	13	24
10	15	22	37
11	19	14	33
12	19	20	39
13	26	13	39
Total firms	134	257	391
Total observations	1,261	1,506	2,767

This table summarises the number of times firm observations occur in the sample. For example, 39 firms have 13 firm-year observations in the sample; 26 of these have been award shortlisted in one of the thirteen years, and 13 have not been shortlisted in any of the thirteen years.

Table 4. Distribution of industry division by award-year.

Table 5. Distribution and overlap of award observations by year.

Award Year	PwC	IRS	IC	AA	Comm	E-com	Award Total
2007	5			3		4	11
	(1)			(0)		(1)
2008	5			3		3	11
	(0)			(0)		(0)
2009	3	7		3		2	12
	(2)	(2)		(2)		(0)
2010	5	9	3	11		2	24
	(3)	(4)	(1)	(3)		(1)
2011	4	7	2			2	12
	(2)	(3)	(0)			(1)
2012	17	7	2		5	4	25
	(7)	(5)	(2)		(0)	(3)
2013	4	9	8		7	4	27
	(1)	(3)	(2)		(0)	(2)
2014	14	6	7		14	2	33
	(8)	(5)	(3)		(4)	(0)
2015	7	10	7		16	29	52
	(6)	(3)	(4)		(13)	(11)
2016	4	8	5		18	19	40
	(3)	(4)	(2)		(14)	(8)
2017	3	13	8		17	19	50
	(1)	(6)	(3)		(12)	(3)
2018	3	10	9		18	27	49
	(2)	(3)	(5)		(12)	(7)
2019	3	7	3		19	30	47
	(3)	(6)	(2)		(15)	(9)
Total observations	77	93	54	20	114	147	393
(Total overlap)	(39)	(44)	(24)	(5)	(70)	(46)

Distribution of the award obervations over the time period 2007–2019 are shown in the last column (note that Table 4 includes these same statistics). This table shows the specific awarding institutions from which the observations originate. The total number of observations in the highlighted columns does not add to ‘award total’ because some observations are shortlisted by two (or more) organisations in the same year. These overlap observations are noted in parenthesis. For example: in 2009 PwC and IR Society both shortlisted Great Portland Estates, PwC and Accountancy Age shortlisted HSBC, and IR Society and Accountancy Age shortlisted Marks & Spencer. Therefore PwC, IR Society and Accountancy Age each had two observations that overlapped with another scheme.

Table 6. Tests of difference before matching

	AWARD = 0							AWARD = 1							Pooled Test of Diff.
Variable	Min	Lower Quart	Med	Upper Quart	Max	Mean	Std Dev	Min	Lower Quart	Med	Upper Quart	Max	Mean	Std Dev	T-test
SIZE	4.93	6.75	7.91	14.12	19.02	9.81	3.75	5.77	8.79	14.90	16.11	19.44	13.04	3.98	15.41
ANALYST	1.00	8.00	13.00	17.00	36.00	12.85	6.11	3.00	14.00	17.00	22.00	35.00	17.50	6.04	13.77
EARN_SUR	0.00	0.17	2.13	6.25	323.65	8.21	28.87	0.00	0.02	0.32	3.00	677.20	7.20	41.20	0.58
EARN_VAR	0.00	0.05	0.11	0.28	569.07	1.79	20.57	0.00	0.06	0.19	0.57	4120.25	13.29	208.87	2.37
LOSS	0.00	0.00	0.00	0.00	1.00	0.09	0.28	0.00	0.00	0.00	0.00	1.00	0.10	0.31	1.04
LOSS_lag1	0.00	0.00	0.00	0.00	1.00	0.09	0.29	0.00	0.00	0.00	0.00	1.00	0.11	0.32	1.27
PRICE_VOL	0.11	0.22	0.27	0.33	54.08	1.85	5.98	0.11	0.19	0.24	0.32	44.09	2.66	6.97	2.38
PERFORM	−104.73	0.09	0.17	0.27	1082.25	1.94	25.79	−58.64	0.08	0.17	0.34	174.95	2.59	13.68	0.48
ΔPERFORM	−348.33	−0.30	0.00	0.11	22.08	−0.60	10.09	−161.70	−0.15	0.00	0.02	60.34	−0.83	10.52	0.42
R&D	−9.21	0.00	0.00	0.00	8.25	0.28	2.18	−7.82	0.00	0.00	0.00	8.16	−0.27	2.31	4.50
COMPLEX	0.00	1.00	2.00	4.00	10.00	2.42	2.16	0.00	0.00	1.00	4.00	10.00	2.03	2.54	3.19
LEVERAGE	0.00	0.05	0.20	0.36	71.30	1.85	7.44	0.00	0.18	0.29	0.45	49.99	3.89	10.16	4.64
TRADE_VOL	9.13	13.03	14.00	14.97	19.63	14.01	1.46	10.95	14.33	15.19	16.07	18.98	15.14	1.34	14.20
PWC	0.00	0.00	0.00	1.00	1.00	0.28	0.45	0.00	0.00	0.00	1.00	1.00	0.45	0.50	6.61
DELOITTE	0.00	0.00	0.00	1.00	1.00	0.28	0.45	0.00	0.00	0.00	0.00	1.00	0.24	0.43	1.58
EY	0.00	0.00	0.00	0.00	1.00	0.13	0.34	0.00	0.00	0.00	0.00	1.00	0.11	0.31	1.36
KPMG	0.00	0.00	0.00	0.00	1.00	0.19	0.39	0.00	0.00	0.00	0.00	1.00	0.14	0.35	2.14
US_GAAP	0.00	0.00	0.00	0.00	1.00	0.02	0.13	0.00	0.00	0.00	0.00	1.00	0.11	0.31	9.58
CO_BLOCK	0.00	0.00	0.00	0.00	74.00	3.45	10.38	0.00	0.00	0.00	0.00	50.00	1.39	6.14	3.80
IC_BLOCK	0.00	0.00	8.00	15.00	64.00	9.47	9.10	0.00	0.00	6.00	10.00	33.00	6.91	6.63	5.30
EMP_BLOCK	0.00	0.00	0.00	0.00	71.00	4.99	12.39	0.00	0.00	0.00	0.00	70.00	2.30	8.55	4.11
OTH_BLOCK	0.00	0.00	0.00	0.00	70.00	1.16	7.23	0.00	0.00	0.00	0.00	40.00	0.27	2.62	2.41
PF_BLOCK	0.00	0.00	0.00	0.00	27.00	0.14	1.47	0.00	0.00	0.00	0.00	12.00	0.34	1.63	2.52
GOV_BLOCK	0.00	0.00	0.00	0.00	70.00	0.46	3.88	0.00	0.00	0.00	0.00	39.00	1.28	4.65	3.71
FOR_SH	0.00	0.00	5.00	11.00	74.00	8.60	13.02	0.00	0.00	6.00	11.00	54.00	7.76	8.79	1.23
ED_AGE	37.00	48.70	51.30	54.00	67.00	51.44	4.41	40.00	50.00	52.00	54.00	62.00	51.91	3.85	1.97
NED_AGE	48.50	57.00	59.30	61.50	72.00	59.31	3.37	51.00	57.00	58.70	61.00	69.00	58.88	2.89	2.38
ED_ED	0.00	1.00	1.60	2.00	4.00	1.65	0.77	0.00	1.50	2.00	2.40	4.00	1.96	0.72	7.38
NED_ED	0.00	1.50	2.00	2.30	4.00	1.95	0.61	0.70	1.90	2.00	2.30	3.80	2.06	0.53	3.53
ED_GENDER	33.00	100.00	100.00	100.00	100.00	95.52	12.56	33.00	100.00	100.00	100.00	100.00	94.14	14.29	1.94
NED_GENDER	20.00	71.40	83.00	100.00	100.00	82.14	15.07	33.00	63.00	71.00	80.00	100.00	71.76	12.66	12.77
ED_NATION	0.00	0.00	0.00	0.00	1.00	0.13	0.26	0.00	0.00	0.00	0.40	1.00	0.19	0.32	4.16
NED_NATION	0.00	0.00	0.00	0.50	1.00	0.26	0.33	0.00	0.00	0.40	0.70	1.00	0.40	0.39	7.32
CEO_CHAIR	0.00	0.00	0.00	0.00	1.00	0.01	0.08	0.00	0.00	0.00	0.00	1.00	0.01	0.09	0.20
ED_RATIO	0.07	0.25	0.33	0.42	0.71	0.34	0.11	0.07	0.22	0.29	0.38	0.57	0.30	0.10	6.26

This table contains (1) descriptive statistics for the subsamples AWARD = 0 and AWARD = 1 and (2) pooled tests of differences between the two subsamples (null hypothesis is that the two subsamples are the same). Two-tailed p-values resulting from parametric (t-statistic) tests of differences are shown. This panel comprises 2,330 firm-year observations of which 393 are award shortlisted. See appendix 2 for variable definitions.

Table 7. Regression analysis: firm-level determinants of high-quality.

	Expected	(1)		(2)
	Sign	Full Regression		Stepwise Regression
SIZE	(+)	0.039	***	0.036	***
		3.80		3.82
ANALYST	(+)	0.007	***	0.006	***
		3.89		3.80
EARN_SUR	(+)	0.000
		0.33
EARN_VAR	(+)	0.000
		0.81
LOSS	(+)	0.032
		1.28
LOSS_lag1	(+)	0.021
		0.85
PRICE_VOL	(−)	0.001
		0.18
PERFORM	(?)	0.000
		0.38
ΔPERFORM	(?)	0.000
		0.53
R&D	(+)	−0.009	***	−0.009	***
		2.69		2.72
COMPLEX	(+)	−0.010	***	−0.009	***
		3.27		2.92
LEVERAGE	(−)	0.001
		1.11
TRADE_VOL	(+)	0.010		0.016	*
		1.10		1.74
PWC	(?)	0.066	**	0.081	***
		2.29		5.74
DELOITTE	(?)	0.001
		0.02
EY	(?)	−0.024
		0.71
KPMG	(?)	−0.040
		1.22
US_GAAP	(?)	0.007
		0.19
CO_BLOCK	(?)	−0.005	***	−0.004	***
		3.58		3.74
IC_BLOCK	(?)	−0.003	**	−0.002	**
		2.24		2.54
EMP_BLOCK	(?)	−0.002	***	−0.002	***
		2.58		2.75
OTH_BLOCK	(?)	−0.010	***	−0.010	***
		3.48		3.58
PF_BLOCK	(?)	0.010	***	0.010	***
		2.69		3.10
GOV_BLOCK	(+)	0.000
		0.01
FOR_SH	(+)	0.001
		0.52
ED_AGE	(?)	−0.005	***	−0.005	***
		2.76		2.73
NED_AGE	(?)	−0.012	***	−0.011	***
		4.50		4.34
ED_ED	(+)	0.042	***	0.044	***
		4.19		4.50
NED_ED	(+)	0.012
		0.89
ED_GENDER	(−)	0.001
		1.34
NED_GENDER	(−)	−0.001	**	−0.001	**
		2.40		2.32
ED_NATION	(+)	0.017
		0.71
NED_NATION	(+)	0.017
		0.75
CEO_CHAIR	(−)	−0.010
		0.12
ED_RATIO	(+)	0.265	***	0.223	***
		3.15		2.71
TIME		YES		YES
IND		YES		YES
Pseudo adj. R-squared		0.242		0.251

Logistic regressions include 2,330 firm-year observations from 2007 to 2019. Statistics shown are marginal effects and t-value. See variable definitions in Appendix 2. The dependent variable (in log-odds) is AWARD (whether the firm has been shortlisted for an annual reporting award in time = t) and there are 393 firm-year observations of AWARD = 1. The F-test p-value for INDUSTRY (TIME) is 0.0513 (<0.0001) in the stepwise regression. Pseudo adjusted r-square is calculated as Shtatland et al. (2011) adjustment 3.

Table 8. Tests of difference after matching.

	AWARD = 0							AWARD = 1							Paired Test of Diff.
Variable	Min	Lower Quart	Med	Upper Quart	Max	Mean	Std Dev	Min	Lower Quart	Med	Upper Quart	Max	Mean	Std Dev	T-test
SIZE	5.56	7.68	10.45	15.14	18.96	11.48	3.96	6.04	7.59	10.61	15.44	18.84	11.56	4.03	0.79
ANALYST	3.00	12.00	16.00	19.00	32.00	15.78	5.60	3.00	12.00	15.00	19.00	35.00	15.58	5.90	0.48
EARN_SUR	0.00	0.07	1.38	5.74	323.65	10.25	37.93	0.00	0.05	1.18	3.64	72.15	4.03	8.54	2.18
EARN_VAR	0.00	0.06	0.13	0.39	286.48	3.74	24.72	0.00	0.06	0.17	0.58	4120.25	29.80	326.06	1.01
LOSS	0.00	0.00	0.00	0.00	1.00	0.06	0.23	0.00	0.00	0.00	0.00	1.00	0.14	0.35	2.70
LOSS_lag1	0.00	0.00	0.00	0.00	1.00	0.08	0.27	0.00	0.00	0.00	0.00	1.00	0.08	0.27	0.00
PRICE_VOL	0.12	0.22	0.26	0.31	35.67	2.28	6.67	0.11	0.21	0.25	0.31	35.10	2.12	6.07	1.00
PERFORM	−1.99	0.10	0.17	0.29	66.37	2.46	8.43	−58.64	0.07	0.17	0.33	174.95	1.87	15.25	0.49
ΔPERFORM	−8.67	−0.24	−0.01	0.01	8.50	−0.07	1.43	−161.70	−0.20	0.00	0.10	17.65	−1.50	13.24	1.37
R&D	−8.52	0.00	0.00	0.00	6.71	−0.35	2.37	−7.20	0.00	0.00	0.00	8.16	−0.07	2.50	1.56
COMPLEX	0.00	0.00	1.00	4.00	10.00	2.09	2.40	0.00	0.00	2.00	4.00	10.00	2.49	2.63	1.41
LEVERAGE	0.00	0.02	0.15	0.33	39.66	1.54	5.89	0.00	0.14	0.29	0.41	48.11	3.09	8.39	2.75
TRADE_VOL	10.79	13.93	14.41	15.11	18.30	14.51	1.26	10.95	13.61	14.58	15.38	17.79	14.54	1.34	0.26
PWC	0.00	0.00	0.00	1.00	1.00	0.36	0.48	0.00	0.00	0.00	1.00	1.00	0.36	0.48	0.00
DELOITTE	0.00	0.00	0.00	1.00	1.00	0.25	0.44	0.00	0.00	0.00	1.00	1.00	0.32	0.47	1.34
EY	0.00	0.00	0.00	0.00	1.00	0.14	0.35	0.00	0.00	0.00	0.00	1.00	0.11	0.31	1.03
KPMG	0.00	0.00	0.00	0.00	1.00	0.16	0.37	0.00	0.00	0.00	0.00	1.00	0.14	0.35	0.47
US_GAAP	0.00	0.00	0.00	0.00	1.00	0.05	0.22	0.00	0.00	0.00	0.00	1.00	0.06	0.24	0.47
CO_BLOCK	0.00	0.00	0.00	0.00	39.00	1.53	5.45	0.00	0.00	0.00	0.00	50.00	1.93	8.01	0.54
IC_BLOCK	0.00	0.00	5.00	10.00	63.00	7.03	8.04	0.00	0.00	6.00	12.00	26.00	7.28	7.04	0.30
EMP_BLOCK	0.00	0.00	0.00	0.00	54.00	3.30	9.94	0.00	0.00	0.00	0.00	70.00	3.04	9.51	0.30
OTH_BLOCK	0.00	0.00	0.00	0.00	14.00	0.30	1.67	0.00	0.00	0.00	0.00	5.00	0.03	0.39	2.01
PF_BLOCK	0.00	0.00	0.00	0.00	5.00	0.16	0.87	0.00	0.00	0.00	0.00	12.00	0.22	1.46	0.50
GOV_BLOCK	0.00	0.00	0.00	0.00	70.00	1.70	9.24	0.00	0.00	0.00	0.00	16.00	0.99	2.85	0.96
FOR_SH	0.00	0.00	5.00	10.00	70.00	7.93	12.99	0.00	0.00	6.00	12.00	54.00	8.19	9.98	0.21
ED_AGE	41.50	49.00	51.30	54.00	66.70	51.74	4.35	40.00	48.50	51.00	54.00	62.00	51.29	4.43	0.98
NED_AGE	51.50	57.30	59.00	61.00	66.50	59.11	2.71	51.90	56.50	58.40	61.00	69.00	58.76	3.15	1.12
ED_ED	0.00	1.00	2.00	2.30	4.00	1.79	0.85	0.00	1.30	2.00	2.00	3.50	1.82	0.71	0.37
NED_ED	0.80	1.60	2.00	2.20	4.00	1.94	0.57	0.70	1.70	2.00	2.40	3.80	2.06	0.59	1.95
ED_GENDER	33.00	100.00	100.00	100.00	100.00	93.81	15.16	33.00	100.00	100.00	100.00	100.00	95.71	12.38	1.20
NED_GENDER	33.30	66.70	75.00	83.30	100.00	76.16	14.79	33.00	67.00	75.00	83.00	100.00	74.95	12.99	1.07
ED_NATION	0.00	0.00	0.00	0.00	1.00	0.15	0.28	0.00	0.00	0.00	0.40	1.00	0.16	0.29	0.50
NED_NATION	0.00	0.00	0.30	0.50	1.00	0.33	0.35	0.00	0.00	0.30	0.60	1.00	0.34	0.35	0.51
CEO_CHAIR	0.00	0.00	0.00	0.00	1.00	0.01	0.11	0.00	0.00	0.00	0.00	0.00	0.00	0.00	1.42
ED_RATIO	0.10	0.25	0.33	0.38	0.56	0.32	0.09	0.10	0.22	0.30	0.38	0.57	0.31	0.10	1.00
DAYS_YE_EA	26.00	50.00	57.00	64.00	80.00	56.60	10.68	30.00	48.00	57.00	62.00	89.00	56.09	10.71	0.47
DAYS_EA_AR	1.00	20.00	27.00	37.00	85.00	28.84	13.19	6.00	19.00	25.00	33.00	74.00	25.60	11.35	2.46
DAYS_YE_AR	54.00	77.00	85.00	93.00	134.00	85.45	13.34	52.00	73.00	81.00	88.00	137.00	81.68	13.63	2.63

This table contains (1) descriptive statistics for the subsamples AWARD = 0 and AWARD = 1 and (2) paired tests of differences between the two subsamples (null hypothesis is that the two subsamples are the same). Parametric (t-statistic) two-tailed tests of differences are shown. This panel comprises 161 matched firm-year observations (322 total). See appendix 2 for variable definitions. DAYS_YE_EA is the number of days between the firm's year-end and the earnings announcement release date; DAYS_EA_AR is the number of days between the earnings announcement and annual report release dates; DAYS_YE_AR is the number of days between the firm's year-end and the annual report release date.

Table 9. Capital market effects of award shortlisting.

	Earnings Announcement Date						Annual Report Publication Date
	(1)		(2)		(3)		(4)		(5)		(6)
Variable	|CAR|		AT		NT		|CAR|		AT		NT
Intercept	0.162	**	0.970		2.860	***	−0.017		1.065		2.295	***
	2.67		1.23		4.09		0.51		1.73		4.28
AWARD	−0.013	***	−0.024		−0.097	**	0.000		0.004		−0.026
	3.53		0.61		2.57		0.18		0.13		0.83
SIZE	−0.008	*	−0.155	***	0.168	***	−0.002		−0.061		0.144	***
	1.89		3.35		3.67		0.98		1.38		3.94
ANALYST	0.001		0.018		0.030	*	0.000		0.008		0.025	**
	0.73		1.27		1.90		0.17		0.64		2.36
EARN_SUR	0.000		−0.001		−0.001		0.000		−0.002	***	−0.001	**
	0.07		0.95		1.08		0.11		2.99		2.21
LOSS	0.013		0.174		−0.256	***	0.001		0.157	*	−0.207	***
	1.43		1.63		2.61		0.19		1.71		3.20
R&D	0.001		−0.023		−0.017		−0.001		0.004		−0.007
	0.74		1.37		0.93		0.41		0.20		0.47
COMPLEX	0.003		0.000		−0.031		0.000		−0.007		−0.028	*
	1.29		0.02		1.50		0.11		0.45		1.96
LEVERAGE	0.000		−0.009		0.007		0.000		−0.006		0.012	***
	0.82		1.50		1.50		1.28		1.54		2.68
TRADE_VOL	0.006		0.252	***	−0.120	***	0.005	**	0.151	***	−0.128	***
	1.43		5.72		2.64		2.22		4.82		4.00
PWC	0.086	**	1.005	**	0.380		0.035		0.584		0.373
	2.25		2.47		1.01		1.39		1.61		1.26
CO_BLOCK	0.000		−0.011		−0.008		0.000		−0.011	*	−0.008
	0.35		1.42		1.00		1.06		1.91		1.62
IC_BLOCK	0.000		0.000		−0.013	**	0.000		−0.002		−0.011	***
	0.55		0.03		2.01		0.55		0.37		2.83
EMP_BLOCK	−0.001		−0.010	**	−0.009	**	0.000		−0.003		−0.005
	1.56		2.41		2.15		1.47		0.96		1.57
OTH_BLOCK	−0.003		−0.004		−0.026		0.001		0.012		−0.017
	1.09		0.15		1.14		1.23		0.65		1.28
PF_BLOCK	0.003		0.028		0.008		0.000		−0.011		−0.013
	1.09		1.06		0.35		0.20		0.63		0.61
ED_AGE	−0.002	**	−0.011		−0.011		0.000		−0.017	***	−0.010	*
	2.10		1.60		1.36		0.67		2.66		1.69
NED_AGE	−0.001		−0.005		−0.028	*	−0.001		−0.009		−0.027	***
	0.60		0.31		1.83		0.85		0.76		2.71
ED_ED	0.004		0.061		0.179	**	0.007		0.087		0.213	***
	0.47		0.78		2.07		1.63		1.36		4.06
NED_ED	−0.001		−0.073		0.017		0.000		−0.092	**	0.026
	0.30		1.42		0.35		0.08		2.16		0.74
NED_GENDER	−0.001		−0.005		−0.012	***	0.000		−0.002		−0.007	***
	2.25		1.43		2.92		0.95		0.74		2.76
ED_RATIO	−0.031		−0.272		0.963	***	0.007		−0.149		0.746	***
	0.93		0.86		2.83		0.42		0.63		3.53
YE_EA	0.000		−0.002		−0.001		0.000		−0.001		0.000
	0.85		0.83		0.25		0.49		0.49		0.16
EA_AR	0.000		−0.003		−0.003		0.000	**	−0.004	**	−0.003
	1.45		1.20		1.28		2.24		1.96		1.57
TIME	YES		YES		YES		YES		YES		YES
IND	YES		YES		YES		YES		YES		YES

* Z > 1.65; ** Z > 1.96; *** Z > 2.58.

This table contains Generalized Estimation Equation regression models for the event study where market-level dependent variables are absolute abnormal returns (|CAR|), absolute trading volume (ATV), and number of trades (NT). The independent variable of interest is the binary AWARD variable. Remaining variables encompass all matching variables plus statistically significant variables from Table 8. The sample comprises 161 matched firm-year observations (322 total). A window of four days (t−2 to +1) is used where t = 0 is the Earnings Announcement or Annual Report publication date. |CAR| is calculated using arithmetic returns (no significant differences using geometric returns).

Table 10. Regression analysis: timeliness of information capture.

	TIMELINESS
Intercept	0.137
	1.05
AWARD	−0.014	*
	1.88
SIZE	−0.009
	1.01
ANALYST	0.000
	0.07
EARN_SUR	0.000	***
	2.89
LOSS	0.049	**
	2.53
R&D	0.002
	0.63
COMPLEX	−0.001
	0.14
LEVERAGE	−0.001
	0.64
TRADE_VOL	0.012
	1.53
PWC	0.068
	0.89
CO_BLOCK	0.001
	0.45
IC_BLOCK	−0.001
	0.49
EMP_BLOCK	−0.001
	0.85
OTH_BLOCK	−0.005
	1.04
PF_BLOCK	0.004
	0.68
ED_AGE	0.000
	0.10
NED_AGE	−0.001
	0.27
ED_ED	0.004
	0.29
NED_ED	0.013
	1.52
NED_GENDER	−0.001
	1.61
ED_RATIO	−0.008
	0.11
YE_EA	0.000
	0.57
EA_AR	0.000
	0.24
TIME	YES
IND	YES

* Z > 1.65; **Z > 1.96; *** Z > 2.58.

This table presents a Generalized Estimation Equation where the dependent variable is TIMELINESS (Beekes and Brown 2006). TIMELINESS captures the speed of share price discovery and approaches zero the quicker information is integrated into share price. The independent variable of interest is the binary AWARD variable. Remaining variables encompass all matching variables plus statistically significant variables from Table 8. The sample comprises 161 matched firm-year observations (322 total).

Table

Award	PwC ‘Excellence in Reporting’	IR Society ‘Best Practice'	ICSA Hermes ‘Best Annual Report’	Communicate Magazine ‘Best Printed Report’ & ‘Best Online Report'	Report Watch
Comprehensive (FTSE100 & 250) or nominated	Comprehensive	Nominated	Comprehensive	Nominated	Nominated
Criteria	‘the judges were seeking excellence across the three pillars of corporate reporting: Content – A holistic balance covering management’s view of the business, its market environment, strategy, business model, risks and performance. Quality – A forward-looking narrative supported by quantified data, targets,benchmarking and performance indicators. Integration – Consistent messaging across elements such as strategy, management actions, performance and reward. Alongside these established attributes, they were also looking for evidence of a fourth: innovation, involving taking a fresh approach to traditional disclosures and exploring new ways to meet stakeholders’ information needs’. (PwC 2014)	‘judges are looking for evidence of an innovative and effective report that plays an integral part in the communication of the strategy and investment case of a company. It should serve as an effective communications tool and provide insight into the company’s main objectives and strategies, the principal risks it faces and how they might affect future prospects. For U.K. listed companies, there will be a focus on the objectives set out in the Financial Reporting Council’s (FRC) Guidance on the Strategic Report issued in June 2014’. (IR Society 2015)	‘an understanding of the links between governance, shareholder value creation, and the avoidance of value destruction; innovative and creative forms of disclosure, which moved away from ‘boilerplate’ reporting that repeated or imitated the language of the Code with little, or no, attempt to explain how the board and company was run; a full description – and explanation– of the business model and the strategy, with key performance indicators and performance against targets; the principal risks to that strategy, the company’s risk appetite and culture, how the risk profile was changing, and how the risks were being managed; joined-up thinking that linked strategy, pay, performance and risk; explanations of the way in which the board ran itself and its committees, and how it took decisions; recognition of having due regard for, and balancing the needs and expectations of, different shareholder and stakeholder priorities … ’ (ICSA 2014)	‘Strategy/Implementation: Explain the approach you took in order to meet your objective(s). What was the strategy? How did the strategy develop? How did the strategy differ from the previous year? What research was carried out and incorporated? What influenced the decision making? How did you implement the strategy? Did you encounter unexpected difficulties? How did you ensure the target audience was reached? How was the report incorporated into the company’s communication output? Innovation: Show off why your work stands out from others. Was the report innovative? If not explain any restrictions faced with the innovation of the report. How did the report fit with the rest of the brand? What creative aspects were incorporated? Include information on ease of access and navigation of the report? Result: Tell about the success of the report: how the initial objectives were met’. (Communicate Magazine 2015)	Best practice areas: 1. Cover/Message/Theme/ Branding 2. Business overview 3. Key figures 4. CEO/Chairman message 5. Business model/ Strategy/Growth drivers 6. Key performance indicators 7. Investor proposition/share information 8. Financial review/MD&A 9. Goals/Targets/Outlooks 10. Risk factors, controls and management 11. Governance and compensation 12. Corporate social responsibility 13. Historical data, charts and ratios 14. Online reporting 15. Style/Design/Layout Grading: A+ First rate; A Excellent; A- Very Good; B+ Sound; B Average; B- Uneven; C+ Common; C Substandard; C- Poor; D Uncompetitive (e.com 2014)
Year-end cut-off date	March 31	March 31	‘the strategy or execution was developed, launched or carried about between January 2013 and June 2014’	Annual reports published before the deadline for nominated awards are accepted (usually August)	December 31
Panel Members (2014)	1. Charles Tilley (chair), CIMA 2. Stephen Haddrill, FRC 3. Angela Knight CBE, Energy U.K. 4. Paul Lee, National Association of Pension Funds. 5. The Right Hon the Lord Jack McConnell 6. Sir Chris Powell, Advertising Standards Board of Finance 7. Andrew Hind CB, Charity Finance 8. Roger Adams, ACCA 9. Jeremy Beeton, SSE plc. 10. Andy Brough, Schroders. 11. Robert Hodgkinson, ICAEW 12. Maggie McGhee, National Audit Office. 13. Melanie McLaren, FRC Liz Murrall, IMA 14. Ian Pearson, IPP Associates Ltd. 15. David Phillips, World Wildlife Fund 16. Lady Susan Rice CBE, Lloyds Banking Group Scotland. 17. Rod Sellers OBE, Seddon Solutions Ltd.	1. Sue Scholes (Chair), Chair of the IR Society 2. Sue Harding, FRC Financial Reporting Laboratory 3. Liz Murrall, U.K. IMA / IA 4. Andrew Ninian, ABI / IA 5. Nigel Sleigh-Johnson, ICAEW 6. Peter Swabey, ICSA 7. Martin Walker, Manchester Business School 8. Catherine Wright, ICSA	1. Dame Alison Carnwath (Chair), Land Securities plc 2. Paul Boniface, The National Trust 3. Andrew Ninian, IMA 4. Professor Andrew Chambers, Management Audit LLP 5. Ruth Pavey FCIS, Capital & Counties Properties PLC 6. Lyn Colloff FCIS, Cobham 7. Frank Curtiss FCIS, RPMI Railpen Investments 8. Sallie Pilot, Black Sun plc 9. Lindsay Driscoll, consultant 10. Nicola Rimmer, Chartered Institute of Internal Auditors 11. Anthony Fitzsimmons, Reputability LLP 12. Deepa Raval, FRC 13. John Gollifer, IR Society 14. Carol Shutkever, Herbert Smith Freehills 15. Chris Hopson, Foundation Trust Network 16. Lara Thomassen, CBI 17. Catherine Howarth, ShareAction 18. Tim Ward, The Quoted Companies Alliance 19. Jo Iwasaki, ICAEW 20. Mark Wearden FCIS, ACCA 21. Paul Lee, National Association of Pension Funds 22. Victoria Whyte FCIS, GlaxoSmithKline plc 23. Gillian Lees, Chartered Institute of Management Accountants 24. Derek Woodward FCIS, Thomas Cook Group plc 25. John Ludlow, AIRMIC 26. Catherine Woods, FRCl	1. Tim Brill, MicroFocus 2. Davis S. Brilleslijper, Delta Lloyd Group 3. Thomas Churchill, Premier Farnell 4. Catherine Colloms, PaddyPower 5. Gary Davies, GlaxoSmithKline 6. Chris Griffiths, Tesco 7. Ian Harding, Kingfisher 8. Basak Kotler, Coca-Cola Hellenic Bottling Company 9. Craig Marks, Halfords 10. Ian McDonald Wood, FutureValue 11. Kate Montgomery, Imagination 12. Paul Nixon, Corporate Eye 13. Helen Parris, G4S plc 14. Martin Riecken, Deutchse Lufthansa AG 15. Andrew Sawers, freelance financial journalist 16. Ian Thornton, ARM 17. Ian Williams, Think Money Group 18. Lisa Williams, Debenhams plc	No external panel. (companies purchase a comprehensive evaluation of their annual report and the grade– A+ to D– is published on the Report Watch website)

Table

Variable	Definition	Pred Sign	Theory
Size (SIZE)	Natural logarithm of market capitalization at the fiscal year end date (Worldscope field 07210)	(+)	Agency theory and legitimacy theory (see Guthrie and Parker 1990). Larger firms tend to be more highly monitored and their reports more widely read therefore large firms benefit the most from increased information disclosure (Diamond and Verrecchia 1991).
Analyst following (ANALYST)	Number of analysts whose earnings estimates are included in the most recent I/B/E/S consensus before the fiscal year end	(+)	Ease of information acquisition increases in firms with high-quality annual report narratives, thereby incentivising analysts to follow firms with high-quality reporting (Lang and Lundholm 1993, 1996)
Absolute earnings surprise (EARN_SUR)	Absolute percentage difference between I/B/E/S actual earnings and the last I/B/E/S consensus forecast prior to the fiscal year end	(+)	Management enhances disclosure when faced with delivering unexpected earnings news to investors (Yuthas et al. 2002).
Earnings variation (EARN_VAR)	Three-year EPS variance (current year and two years previous) as derived from Worldscope EPS data (field 05210)	(+)	Firms with high earnings variation have more potential for information asymmetry between managers and investors (Li 2010) and higher potential for disclosure quality. Higher variability in earnings is expected to result in high-quality annual report narratives to convey revised information on corporate performance and future prospects.
Earnings loss (LOSS; LOSS_lag1)	Indicator variable taking the value of one if net income at time t (time t–1) is negative and zero otherwise	(+)	Losses make forecasting future returns problematic because investors cannot assume earnings permanence in forecasting models (Schleicher et al. 2007), therefore firms may increase disclosure to ease investor forecasting.
Price volatility (PRICE_VOL)	Annualized monthly stock return volatility for the 12 month period ending on the last day of the earnings announcement month (Worldscope field 08806)	(−)	High-quality disclosure reduces uncertainty (and mitigates perceived risk) which decreases the price impact of information on firm performance (Lang and Lundholm 1993, Bushee and Noe 2000). Additionally, disclosure increases stock liquidity which reduces the price impact of large trades (Diamond and Verrecchia 1991).
Performance (PERFORM; ΔPERFORM)	Return on equity as taken from Worldscope (field 08302) ΔPERFORM is the percentage change in ROE from time t-1 to time t	(?)	The obfuscation hypothesis (see Merkl-Davies and Brennan 2007) predicts that poorly performing firms will produce disclosures with reduced understandability: a negative association.
			Users of information assume low value or high risk in the absence of disclosure (Beyer et al. 2010). Poor performance may be thoroughly disclosed and discussed at the annual report date to avoid non-disclosure: a positive association.
Intangibles (R&D)	Natural logarithm of R&D spending (Worldscope field 01201)	(+)	Intangibles represent non-saleable commodities that are difficult to value and not well represented in the financial statements (Grilliches 1995). As such, narrative sections of annual reports provide an outlet to inform investors about changes to the nature and value of intangible assets.
Operational complexity (COMPLEX)	Count of business segments with total assets information (Worldscope fields 19503, 19513, … 19593)	(+)	Complex information requires complex disclosures which require care to be intelligibly conveyed (Li 2010)
Leverage (LEVERAGE)	Is total debt as a percentage of total assets (Worldscope field 08236)	(−)	Agency theory suggests that increased leverage results in additional risk for shareholders as debtholders price-protect themselves. Therefore managers have more incentive to provide a higher level of disclosure to shareholders (Jensen and Meckling 1976, Hossain et al. 1995): a positive association.
			However, leverage may reduce disclosure because agency costs are reduced by debt covenants rather than by increased disclosure in annual reports (Eng and Mak 2003): a negative association.
Average trading volume (TRADE_VOL)	Average annual trading volume over the 52-week period ending at the fiscal year-end date (Thompson-Reuters ID 85695)	(+)	If public disclosure reduces information asymmetry, it may reduce the potential for non-professional investors to assume information from large trades (Diamond and Verrecchia 1991, Healy et al. 1999). Therefore, there is a reduction in the price impact of trades which may draw increased average trading volume to firms with high-quality public disclosure (Bushee and Noe 2000).
Cross-listing in the U.S. (US_GAAP)	Indicator variable equal to one if the firm is cross-listed in the U.S. and zero otherwise	(+)	Firms that cross list in the U.S. subject themselves to additional disclosure requirements (i.e. reconciliation to U.S. GAAP). Additionally, these firms are more visible and may face higher scrutiny from investors and auditors. Therefore, cross listing firms may produce enhanced narrative disclosures (Coffee 2002, Lang et al. 2003).
PWC, DELOITTE, EY and KPMG	Indicator variables equal to one if the annual report is audited by PwC, Deloitte, Ernst&Young or KPMG respectively and zero otherwise	(?)	Firms may choose an auditor that has specialist knowledge to enhance overall firm disclosure, as evidenced in the AIMR-FAF rankings (Dunn and Mayhew 2004).
Blockholdings (NOGOV)	CO_BLOCK (company cross-holding blocks: datastream NOSHCO), IC_BLOCK (investment company blocks: datastream NOSHIC), EMP_BLOCK (employee blocks: datastream NOSHEM), OTH_BLOCK (other blocks: datastream NOSHOF), and PF_BLOCK (pension fund blocks: datastream NOSHPF) where a blockholder is defined as holding over 5% of outstanding shares at the firm's fiscal year end	(?)	Institutional investors may be drawn to firms with low information asymmetry, and therefore high liquidity (Diamond and Verrecchia 1991, Core 2001): a positive association.
			When shareholders are diffused, more monitoring is required (Eng and Mak 2003). Additionally, institutional investors may be put-off by public disclosures that reduce the value of their private information set:^a a negative association.
Government blockholdings (GOV_ BLOCK)	Government held blockholdings (datastream NOSHGV)	(+)	Firms with government ownership tend to have objectives that are value/society-oriented and conflict with commercial objectives. Because of conflicting interests, the firm may have an increased need to communicate with other shareholders (Eng and Mak 2003).
Foreign investors (FOR_SH)	Percentage of shares held by foreign investors at the fiscal year end (datastream NOSHFR)	(+)	Foreign investors are at an informational disadvantage and rely more heavily on narrative information released by the firm and foreign analysts to close the gap (Clatworthy and Jones 2008)
Board characteristics	Boardex variables:	(?)	Certain board characteristics potentially mitigate agency conflicts between management and shareholders (Hermalin and Weisbach 1998, Xie et al. 2003) resulting in more timely and balanced public disclosures (Beekes et al. 2015).
	ED_AGE (NED_AGE) is the average age of executive (non-executive) directors on the board;
	ED_ED (NED_ED) is the average number of qualifications held by executive (non-executive) directors;
	ED_GENDER (NED_GENDER) is the percentage of executive (non-executive) directors that are male;
	ED_NATION (NED_NATION) is foreign representation in executive (non-executive) directors where zero is fully domestic and one is fully foreign;
	CEO_CHAIR is an indicator variable equal to one in the case of CEO/chairman duality and zero otherwise;
	ED_RATIO is the number of executive directors divided by the total number of directors
Time	There are eight year (TIME) indicator variables for TIME, one for each sample year (2007–2014)	(?)	Corporate narrative reporting evolves over time, therefore differences in the definition of narrative reporting quality may exist within the sample period (2007–2014). Additionally, economic events (i.e. financial crisis of 2009) and industry-specific events (i.e. BP oil spill of 2010) are likely to affect the level of firm disclosure and stock prices.
Industry	There are nine industry (IND) indicator variables, representing the nine SIC industry divisions	(?)	The potential importance of industry factors stems from institutional theory, whereby firms operate within the norms of their comparable group in order to reduce scrutiny by stakeholder groups (Meyer and Rowan 1977, Bansal and Clelland 2004). Industries exhibit herding behaviour in disclosure based on the number of firms in the industry, amount of industry versus firm-specific information, and degree of shared knowledge (Dye and Sridhar 1995). Specifically, firms in competitive industries may disclose less (presumably proprietary) information (Verrecchia and Weber 2006).

^a Wagenhofer (2004, p. 26) considers that availability of public information may reduce the total information available to investors because it reduces incentives for professional investors to acquire private information. Therefore, professional (institutional) investors may prefer investment in firms where they have an opportunity to profit from their private information sets.

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