Comments on: 'Results management' — detection and diagnosis using Benford's Law http://landshape.org/enm/results-management-detection-and-diagnosis-with-benfords-law/ The Power of Numeracy Wed, 16 May 2012 18:37:00 +0000 hourly 1 http://wordpress.org/?v=3.3.2 By: 1st page killer earningsreview http://landshape.org/enm/results-management-detection-and-diagnosis-with-benfords-law/#comment-13168 1st page killer earningsreview Tue, 14 Dec 2010 07:27:00 +0000 http://landshape.org/enm/?p=75#comment-13168 Thanks for this information. Thanks for this information.

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]]> By: Niche Modeling » Results Management http://landshape.org/enm/results-management-detection-and-diagnosis-with-benfords-law/#comment-5835 Niche Modeling » Results Management Fri, 07 Jul 2006 18:04:30 +0000 http://landshape.org/enm/?p=75#comment-5835 [...] What is ‘results management’? Accountants and auditors are often concerned with various kinds of alteration of figures, a practice euphemistically called ‘earnings management’. For example in “An Assessment of the Change in the Incidence of Earnings Management around the Enron-Andersen Episode” - Mark Nigrini In 2001 Enron filed amended financial statements setting off a chain of events starting with its bankruptcy filing and including the conviction of Arthur Andersen for obstruction of justice. Earnings reports released in 2001 and 2002 were analyzed. The results showed that revenue numbers were subject to upwards management. Enron’s reported numbers are reviewed and these show a strong tendency towards making financial thresholds. Benford’s law which is a conjecture concerning the expected frequency of digits in unmanaged data, is useful for detecting fraud and other forms of results management. I have posted on some results applied to time series data here, and here. An R module used for analysing these time-series data is available from this site here. However, study of digit frequency only captures a part of what could be termed ‘results management’. As the goal in science, as in accounting, is an objective statements of results, all forms of ‘results management’ are to be deplored. Here are some practices that I have seen, or would consider to be ‘results management’. [...] [...] What is ‘results management’? Accountants and auditors are often concerned with various kinds of alteration of figures, a practice euphemistically called ‘earnings management’. For example in “An Assessment of the Change in the Incidence of Earnings Management around the Enron-Andersen Episode” – Mark Nigrini In 2001 Enron filed amended financial statements setting off a chain of events starting with its bankruptcy filing and including the conviction of Arthur Andersen for obstruction of justice. Earnings reports released in 2001 and 2002 were analyzed. The results showed that revenue numbers were subject to upwards management. Enron’s reported numbers are reviewed and these show a strong tendency towards making financial thresholds. Benford’s law which is a conjecture concerning the expected frequency of digits in unmanaged data, is useful for detecting fraud and other forms of results management. I have posted on some results applied to time series data here, and here. An R module used for analysing these time-series data is available from this site here. However, study of digit frequency only captures a part of what could be termed ‘results management’. As the goal in science, as in accounting, is an objective statements of results, all forms of ‘results management’ are to be deplored. Here are some practices that I have seen, or would consider to be ‘results management’. [...]

]]> By: admin http://landshape.org/enm/results-management-detection-and-diagnosis-with-benfords-law/#comment-5834 admin Fri, 02 Jun 2006 14:19:26 +0000 http://landshape.org/enm/?p=75#comment-5834 Hi Larry. Nigrini developed an index for financial figures that is supposed to diagnose rounding, either up or down. I have implemented it in the package already, so it may be possible to answer the question about rounding of age in deaths using that. Hi Larry. Nigrini developed an index for financial figures that is supposed to diagnose rounding, either up or down. I have implemented it in the package already, so it may be possible to answer the question about rounding of age in deaths using that.

]]> By: admin http://landshape.org/enm/results-management-detection-and-diagnosis-with-benfords-law/#comment-6164 admin Fri, 02 Jun 2006 14:19:00 +0000 http://landshape.org/enm/?p=75#comment-6164 Hi Larry. Nigrini developed an index for financial figures that is supposed to diagnose rounding, either up or down. I have implemented it in the package already, so it may be possible to answer the question about rounding of age in deaths using that. Hi Larry. Nigrini developed an index for financial figures that is supposed to diagnose rounding, either up or down. I have implemented it in the package already, so it may be possible to answer the question about rounding of age in deaths using that.

]]> By: Larry Huldén http://landshape.org/enm/results-management-detection-and-diagnosis-with-benfords-law/#comment-5833 Larry Huldén Fri, 02 Jun 2006 08:01:55 +0000 http://landshape.org/enm/?p=75#comment-5833 This checking of digit distribution is very interesting. Availability of the original measurements is really important. I think that there is an increasing need for statistical checking of very big data sets in different ways. The problems may arise in systematic "errors" or varying rounding effects. I am not thinking of typing errors, interpreting errors of hand written texts or corresponding errors which is a problem of its own. I have an interesting data set of death causes of nearly two million people from 1750 to 1850 in Finland. The death causes have been typed in by hundreds (or thousands) of amateurs interested in tracing there relatives. All the data is available on internet. When checking for the yearly age distribution of different death causes I observed that there was a systematically higher representation of the age classes 20, 30, 40, 50, 60 and so on. From that we can expect that in some cases the exact age of the people was not known, so the priest wrote a "proxy" for the age. I don't know if the rounding is biased upwards or downwards. This causes some problems in detailed analysis of rare death causes. I can only statistically adjust for the age classes. We used the raw data unchanged in the study of malaria in Finland when we compared malaria with some other different diseases in the study. The effect of the deviating age classes are visible in the graphs available at http://www.malariajournal.com/content/4/1/19 The results for malaria are not expected to have been affected by this problem because we think that the bias has the same distribution on each disease. This checking of digit distribution is very interesting. Availability of the original measurements is really important.
I think that there is an increasing need for statistical checking of very big data sets in different ways. The problems may arise in systematic “errors” or varying rounding effects. I am not thinking of typing errors, interpreting errors of hand written texts or corresponding errors which is a problem of its own.
I have an interesting data set of death causes of nearly two million people from 1750 to 1850 in Finland. The death causes have been typed in by hundreds (or thousands) of amateurs interested in tracing there relatives. All the data is available on internet. When checking for the yearly age distribution of different death causes I observed that there was a systematically higher representation of the age classes 20, 30, 40, 50, 60 and so on. From that we can expect that in some cases the exact age of the people was not known, so the priest wrote a “proxy” for the age. I don’t know if the rounding is biased upwards or downwards. This causes some problems in detailed analysis of rare death causes. I can only statistically adjust for the age classes.
We used the raw data unchanged in the study of malaria in Finland when we compared malaria with some other different diseases in the study. The effect of the deviating age classes are visible in the graphs available at http://www.malariajournal.com/content/4/1/19
The results for malaria are not expected to have been affected by this problem because we think that the bias has the same distribution on each disease.

]]> By: Larry Huldén http://landshape.org/enm/results-management-detection-and-diagnosis-with-benfords-law/#comment-6163 Larry Huldén Fri, 02 Jun 2006 08:01:00 +0000 http://landshape.org/enm/?p=75#comment-6163 This checking of digit distribution is very interesting. Availability of the original measurements is really important. I think that there is an increasing need for statistical checking of very big data sets in different ways. The problems may arise in systematic "errors" or varying rounding effects. I am not thinking of typing errors, interpreting errors of hand written texts or corresponding errors which is a problem of its own. I have an interesting data set of death causes of nearly two million people from 1750 to 1850 in Finland. The death causes have been typed in by hundreds (or thousands) of amateurs interested in tracing there relatives. All the data is available on internet. When checking for the yearly age distribution of different death causes I observed that there was a systematically higher representation of the age classes 20, 30, 40, 50, 60 and so on. From that we can expect that in some cases the exact age of the people was not known, so the priest wrote a "proxy" for the age. I don't know if the rounding is biased upwards or downwards. This causes some problems in detailed analysis of rare death causes. I can only statistically adjust for the age classes. We used the raw data unchanged in the study of malaria in Finland when we compared malaria with some other different diseases in the study. The effect of the deviating age classes are visible in the graphs available at http://www.malariajournal.com/content/4/1/19 The results for malaria are not expected to have been affected by this problem because we think that the bias has the same distribution on each disease. This checking of digit distribution is very interesting. Availability of the original measurements is really important.
I think that there is an increasing need for statistical checking of very big data sets in different ways. The problems may arise in systematic “errors” or varying rounding effects. I am not thinking of typing errors, interpreting errors of hand written texts or corresponding errors which is a problem of its own.
I have an interesting data set of death causes of nearly two million people from 1750 to 1850 in Finland. The death causes have been typed in by hundreds (or thousands) of amateurs interested in tracing there relatives. All the data is available on internet. When checking for the yearly age distribution of different death causes I observed that there was a systematically higher representation of the age classes 20, 30, 40, 50, 60 and so on. From that we can expect that in some cases the exact age of the people was not known, so the priest wrote a “proxy” for the age. I don’t know if the rounding is biased upwards or downwards. This causes some problems in detailed analysis of rare death causes. I can only statistically adjust for the age classes.
We used the raw data unchanged in the study of malaria in Finland when we compared malaria with some other different diseases in the study. The effect of the deviating age classes are visible in the graphs available at http://www.malariajournal.com/content/4/1/19
The results for malaria are not expected to have been affected by this problem because we think that the bias has the same distribution on each disease.

]]> By: admin http://landshape.org/enm/results-management-detection-and-diagnosis-with-benfords-law/#comment-5832 admin Thu, 01 Jun 2006 16:04:20 +0000 http://landshape.org/enm/?p=75#comment-5832 I think there is a lot of results management out there. I wonder what the digit frequency of the quelquaya data would look like? I don't intend the analysis to be restricted to digit frequency. Other tests could be included. One of the main reasons I got into this was to look at the WCDP archive. Imagine something that could churn through all the paleo data for suspect data and diagnose its origin. I think there is a lot of results management out there. I wonder what the digit frequency of the quelquaya data would look like? I don’t intend the analysis to be restricted to digit frequency. Other tests could be included.

One of the main reasons I got into this was to look at the WCDP archive. Imagine something that could churn through all the paleo data for suspect data and diagnose its origin.

]]> By: admin http://landshape.org/enm/results-management-detection-and-diagnosis-with-benfords-law/#comment-6162 admin Thu, 01 Jun 2006 16:04:00 +0000 http://landshape.org/enm/?p=75#comment-6162 I think there is a lot of results management out there. I wonder what the digit frequency of the quelquaya data would look like? I don't intend the analysis to be restricted to digit frequency. Other tests could be included. One of the main reasons I got into this was to look at the WCDP archive. Imagine something that could churn through all the paleo data for suspect data and diagnose its origin. I think there is a lot of results management out there. I wonder what the digit frequency of the quelquaya data would look like? I don’t intend the analysis to be restricted to digit frequency. Other tests could be included.

One of the main reasons I got into this was to look at the WCDP archive. Imagine something that could churn through all the paleo data for suspect data and diagnose its origin.

]]> By: Steve McIntyre http://landshape.org/enm/results-management-detection-and-diagnosis-with-benfords-law/#comment-5831 Steve McIntyre Thu, 01 Jun 2006 15:36:47 +0000 http://landshape.org/enm/?p=75#comment-5831 David, you may notice a familiar name in Hans' note. I was just getting started at looking at proxies and this was one of the first puzzling patterns that I noticed. Hans solved the problem. It was amazing that the actual measurement had been superceded by the transformed data and, as I recall, Hans was never able to get Thompson to provide the original data. David, you may notice a familiar name in Hans’ note. I was just getting started at looking at proxies and this was one of the first puzzling patterns that I noticed. Hans solved the problem.

It was amazing that the actual measurement had been superceded by the transformed data and, as I recall, Hans was never able to get Thompson to provide the original data.

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