With regard to Jeff’s post here.
The data source is here.
Jeff quotes Mandani’s blog claim:
The World Bank’s Investment Climate Department (CIC) has reviewed the recent literature on the relationship between restrictive regulation, corruption and business environment reforms, finding that corruption is positively correlated with restrictive regulation.
Jeff disagrees with Mandani. Here is Jeff’s hypothesis
Correlation does not imply causation. When two events A and B are correlated, one of the following is true:
1. A caused B
2. B caused A
3. Some third factor C caused both A and B
4. A and B happening together are just a coincidence.
The correlation appears significant enough that #4 is unlikely.
It also seems unlikely that the length of time it takes to start a business would cause corruption. Correct me if I’m wrong here.
That leaves either #1 or #3.
I hereby hypothesize that #3 is the culprit, and further that factor C is the power brokering-rich environment resulting from a too-large government.
Jeff thinks that the other factor is “too-large government” which results in a “power brokering-rich environment”. I suppose this means that if the government is too large, corporations will use the government to create regulation to benefit themselves and therefore, result in corruption. I take it that Jeff’s solution would mean a small government which would, in theory, keep large corporations from getting corrupt regulations that benefit themselves. Additionally, in true Austrian School economics fashion, if the government is small the free-market will work more efficient over time and, I assume the conclusion would be, result in less corruption in the system (and certainly in less booms and busts according to Austrian economics). If this is the case, the problem with the purity of the Austrian utopian dream is that this data does not back up that claim. To the contrary, this data counters that claim.
Here is my hypothesis:
Jeff is right with regard to #3 being the culprit. However, Jeff is wrong about the specific other factor (C).
First, I have graphed all the data that the World Bank has accumulated based on their 2011 data, the latest data they provide. You can download their data with my added graphed sheets here. They have 5 benchmarks that they measure for 215 countries:
Political Stability, Government Effectiveness, Regulatory Quality, Control of Corruption, Voice and Accountability
Each of the benchmarks are defined above the graphs and the definitions can be found here.
Each benchmark spans the approximate range from -2.5 to +2.5. Estimates range from approximately -2.5 (weak) to 2.5 (strong).
Each graph shows the data sorted by one benchmark, one column only, from lowest value to highest value. The other benchmarks on the graph falls where they may. We will call the sorted column benchmark the dependent variable as it is the outcome we are comparing to our non-sorted benchmarks, the independent variables. The sorted benchmark for each graph is shown as the thickest line on each graph. Linear trend lines are displayed for each of the other, non-sorted, benchmarks for each graph. This methodology will show the relationship of the other independent variable benchmarks, to the dependent variable, the sorted benchmark, to determine which of the independent variable benchmarks might have a causal relationship to the sorted, dependent variable benchmark. We will also look for any relationships we can see of the benchmarks to each other. Also, we should try to see if Jeff’s hypothesis concerning “too-large government” shows a pattern in any of the dependent variables tested.
What the data shows:
If each of the benchmarks are sorted from low to high, the other non-sorted benchmarks trend lines linearly follow the sorted benchmark upwards. This would indicate that each of the benchmarks play a role in improving the results of the others or, put another way, there is no necessary cause and effect relation established by this data to only one or only some of the independent variable benchmarks to the dependent variable benchmark. All of the independent variable benchmarks appear to effect the dependent variable benchmark causally. For example, less corruption results when improvements are made in political stability, government effectiveness, and voice and accountability and not just regulatory quality. The “Control of Corruption” graph shows that the “Regulatory Quality”, independent variable is not a factor of regulation per se but of political stability, government effectiveness, regulatory quality, control of corruption, voice and accountability. In fact, there is nothing in the data about ‘regulation’ as too much or too little regulation but ‘regulation quality’. Additionally, this data does not add credence to the Austrian School’s claim that the free market is able to regulate itself (if that is indeed the claim of the purist fundamentalists). Neither does this data show any singular correlation to the “restrictiveness” of regulations (“regulation quality”) to corruption. If it did, some (perhaps one could argue some but not all of the benchmarks are overlapping to “regulation quality”) or all of the other benchmark trend lines would not have a positive slope. For example, if political stability is decreased, it seems to indicate that corruption goes up as well. There does not appear to be a singular benchmark that is independent from the others with regard to government corruption (“Control of Corruption”).
Additionally, if you look at the countries that are doing better (closer to 2.5) you will see no correlation between big and small countries or governments. This would seem to indicate the Jeff’s hypothesis is wrong with regard to the absolute or relative size of the government. Since all the countries will not fit on the horizontal axis without making the graph too big I will list where the United States rank is for each benchmark (N/As are not included) and the countries that are ahead of us (closer to 2.5):
Political Stability 136 out of 213
CYPRUS, MONGOLIA, CHILE, ITALY, ESTONIA, MACAO SAR, CHINA, COSTA RICA, FRANCE, OMAN, LITHUANIA, PUERTO RICO, MARTINIQUE, PORTUGAL, CAPE VERDE, HUNGARY, GUAM, SLOVENIA, SAMOA, GERMANY, BHUTAN, AUSTRALIA, ST. LUCIA, ST. VINCENT AND THE GRENADINES, MAURITIUS, BELGIUM, NAMIBIA, TAIWAN, CHINA, URUGUAY, UNITED ARAB EMIRATES, HONG KONG SAR, CHINA, SLOVAK REPUBLIC, TONGA, JAPAN, SEYCHELLES, AMERICAN SAMOA, ANTIGUA AND BARBUDA, VIRGIN ISLANDS (U.S.), MALTA, BERMUDA, IRELAND, MONACO, NAURU, PALAU, SAN MARINO, BOTSWANA, CANADA, POLAND, ST. KITTS AND NEVIS, DENMARK, CZECH REPUBLIC, BAHAMAS, THE, BRUNEI DARUSSALAM, NETHERLANDS, VANUATU, AUSTRIA, SINGAPORE, QATAR, ICELAND, DOMINICA, MICRONESIA, FED. STS., SWEDEN, SWITZERLAND, BARBADOS, NETHERLANDS ANTILLES (FORMER), ARUBA, LUXEMBOURG, ANDORRA, KIRIBATI, TUVALU, NORWAY, NEW ZEALAND, FINLAND, CAYMAN ISLANDS, JERSEY, CHANNEL ISLANDS, LIECHTENSTEIN, ANGUILLA, GREENLAND
Government Effectiveness 188 out of 212
IRELAND, JERSEY, CHANNEL ISLANDS, BARBADOS, ANDORRA, ANGUILLA, CYPRUS, GERMANY, UNITED KINGDOM, ICELAND, AUSTRIA, BELGIUM, HONG KONG SAR, CHINA, LUXEMBOURG, AUSTRALIA, LIECHTENSTEIN, NORWAY, NETHERLANDS, CANADA, SWITZERLAND, NEW ZEALAND, SWEDEN, SINGAPORE, DENMARK, FINLAND
Regulatory Quality 195 out of 212
LIECHTENSTEIN, GERMANY, CHILE, ANDORRA, UNITED KINGDOM, SWITZERLAND, IRELAND, CANADA, FINLAND, AUSTRALIA, SINGAPORE, SWEDEN, NETHERLANDS, LUXEMBOURG, HONG KONG SAR, CHINA, NEW ZEALAND, DENMARK
Control of Corruption 182 out of 212
URUGUAY, ANTIGUA AND BARBUDA, BERMUDA, ANGUILLA, ANDORRA, CAYMAN ISLANDS, BAHAMAS, THE, AUSTRIA, IRELAND, JAPAN, FRANCE, UNITED KINGDOM, CHILE, BELGIUM, GERMANY, BARBADOS, LIECHTENSTEIN, HONG KONG SAR, CHINA, ICELAND, CANADA, SWITZERLAND, SINGAPORE, AUSTRALIA, NORWAY, NETHERLANDS, LUXEMBOURG, FINLAND, SWEDEN, NEW ZEALAND, DENMARK
Voice and Accountability 184 out of 214
ST. VINCENT AND THE GRENADINES, MARSHALL ISLANDS, SAN MARINO, ST. KITTS AND NEVIS, PALAU, FRANCE, BARBADOS, ST. LUCIA, JERSEY, CHANNEL ISLANDS, GREENLAND, ARUBA, RÉUNION, UNITED KINGDOM, GERMANY, IRELAND, ANDORRA, BELGIUM, AUSTRIA, CANADA, AUSTRALIA, ICELAND, NETHERLANDS, NEW ZEALAND, FINLAND, LIECHTENSTEIN, LUXEMBOURG, SWEDEN, DENMARK, NORWAY, SWITZERLAND
A few of my comments:
There are multiple reasons for corruption and it is way too simplistic to blame it on ‘regulation’ (in regard to more or less) alone. It may be fair to suggest that ‘bad’ or ineffective regulation could be one factor in increasing corruption but the data does not independently verify this to be the only factor. We should look at how the World Bank defines corruption:
Control of corruption captures perceptions of the extent to which public power is exercised for private gain, including both petty and grand forms of corruption, as well as “capture” of the state by elites and private interests.
Corporatism = Corruption
Their definition is probably the definition of corporatism (see my related essay on corporatism). By definition, corporatism is corruption. In this case, corporatism and corruption is effectively a tautology. However, the definition does not prove the case, the data does.
Corporatism does not necessarily lead to corruption if you believe the Supreme Court of the United States
This data cannot be contrived to make the claim that regulatory quality alone leads to corruption (or its effective tautological definition in this case – corporatism). It is possible to think that “corporations are people too” and they may actually have the best interest of their communities in addition to the best interest of their bottom line (as the ‘clean coal’ campaign would have us believe1).
Regulation as defined by ‘restricting effectiveness’ does not have to be done by the government and many times is not done by the government
If the free market is to decide there will be large corporations and small businesses. Large corporations can effectively ‘regulate’ the market with or without the government as I have made the case elsewhere. The contention of the Austrians is that this type of private ‘free market regulation’ can be overcome by competition. This may or may not be the case. I would think some of the other benchmarks cited here like “Voice and Accountability” might have an impact on this but this is not demonstrated by the data. Additionally, very large multi-national corporations can effectively evade many regulations and taxes of any particular government by locating their operations in more ‘regulatory or tax friendly’ countries and thus create competitive advantages that would be difficult to overcome in the ‘real’ world.
What this data does not show
This data does not show how regulation may actually reduce corruption (i.e., vis-à-vis conflict of interest banking regulations, bribery, loan sharking and theft laws, abolishing slavery, outlawing child labor, ruining the environment, aircraft maintenance, lead based toys, etc.). If, by definition, public regulation is corrosive and the private market cannot be corrosive to market economies, we may have Austrian ideological purity but restraint of corruption is another issue altogether.
With these points in mind, I personally would conclude that corporatism may lead to corruption but that is not substantiated by this data, by the Supreme Court, by the Republican Party, by public policy alone (without ‘free market’, self-regulation also restricting effectiveness). It is also not apparent by this data that corruption may actually be restricted by public policy.
There are countries2 with much smaller and larger governments that are doing better than the United States regarding the benchmarks relative to their size and government spending versus GDP. If you will notice on the “Control of corruption” benchmark there are countries doing better than us like the “government controlled” health care countries of Canada, United Kingdom and France, the “Euro-Socialists”, and even the king of government bureaucracies, communist China (Hong Kong). I believe China is doing better on all the benchmarks except “Voice and Accountability” than the United States in addition to many of the “Euro-Socialists” and the government controlled health care countries. In my opinion, this disproves Jeff’s hypothesis that corruption (as defined by corporatism) is caused by the size of government vis-à-vis public policy regulation.
What we should all learn:
If an ideology makes short shrift of data in order to validate itself, the ideology functions like a religious dogma not like a falsifiable scientific claim. To the degree that we help each other become more rational (I include myself most of all) is to the same degree that we will have a real and positive effect on our community and help each other become better critical thinkers.
Governance consists of the traditions and institutions by which authority in a country is exercised. This includes the process by which governments are selected, monitored and replaced; the capacity of the government to effectively formulate and implement sound policies; and the respect of citizens and the state for the institutions that govern economic and social interactions among them.
A Failed National Security Strategy
The current Administration’s most recent National
Security Strategy reflects the extreme elements
in its liberal domestic coalition.
…
Finally, the strategy subordinates our national
security interests to environmental, energy, and
international health issues, and elevates “climate
change” to the level of a “severe threat” equivalent to
foreign aggression. The word “climate,” in fact, appears
in the current President’s strategy more often
than Al Qaeda, nuclear proliferation, radical Islam,
or weapons of mass destruction.
I’m not sure I agree with your methodology. In order to test my original hypotheses — that size of government impacts corruption and regulatory barriers — I would like to have seen parameters such as length of time it takes to start a business, number of regulations, and level of corruption, plotted on the y-axis against size of government (in percent of GDP) along the x-axis. I can’t look at the charts you’ve provided (kudos for doing all that work, though) and get the same information out of it. You may very well be right, but I’m having a hard time seeing it.
Part of the argument was that the data was not sufficient to draw the conclusion about regulation and corruption that you and Mandani wanted to make. Here is a summary of what the data shows relative to you and Mandani’s argument:
1. Mandani ‘s argument that the “World Bank’s Investment Climate Department (CIC) has reviewed the recent literature on the relationship between restrictive regulation, corruption and business environment reforms, finding that corruption is positively correlated with restrictive regulation” erred in two ways: 1) Mandani argues that “restrictive regulation” and corruption is positively correlated. However, the World bank defines its regulatory data this way – “Regulatory Quality – Regulatory quality captures perceptions of the ability of the government to formulate and implement sound policies and regulations that permit and promote private sector development.” It is not “restrictive regulation” but quality of regulation that is tracked by the data. Regulation can be restrictive to private sector development and STILL promote sound public policy. For example, pollution standards can be restrictive to private sector development and STILL promote sound public policy unless you are willing to make the case that any pollution standards should be done away with. However, this is an extreme (and Austrian market fundamentalist idealism) position that most people and the World Bank would not endorse or assume to be the case in their data tracking and is no way indicated by their definition. 2) There is no way that the data shows that “Regulation Quality” alone, by itself, promotes corruption. The charts I showed make the case that taking one data benchmark by itself like “Regulation Quality” even if it were the erroneous definition of “restrictive regulation” could not be isolated from the other benchmarks as a single cause. This is clearly demonstrated by the data.
2. Your argument claims that the other factor is “too-large government” which results in a “power brokering-rich environment”. There are clearly specific examples of larger governments (both absolute and relative to GDP) that are ranked higher than the US in “Regulation Quality” which are communist, “Euro-socialist” and government run health care AND have better “Control of Corruption” than the US. If you are making an absolute argument that any time there is a “too-large government” there is a “power brokering-rich environment” which leads to more corruption, there are specific and many examples in the data which I pointed out that directly contradict that unqualified hypothesis. If strong examples can be provided that contradict an absolute claim then you must either concede the hypothesis or deny the principle of contradiction. Additionally, the claim that the data is not sufficient to make the claim you want to make is exactly my argument as well in that “power brokering-rich environment” which I assume would be the corporatist oriented “Control of Corruption” benchmark cannot be isolated (at least from the actual data point of view) from the other benchmarks. The most you could claim from the data is that all the benchmarks play a role in corporatism not one single benchmark like “Regulation Quality” (which is not what I think you would like it to be anyway – i.e., too much government regulation or too much “restrictive regulation”.
Regulation and size of government are both the wrong variables. The key factor is official discretion, since corruption is the market for official discretion. Scandinavia has big government and low corruption because its regulation is mostly explicit, with little official discretion.
I would also include the level of banned transactions (not the same as regulated ones). Command economies tend to end up with very high levels of corruption because they have lots of official discretion and lots of banned transactions.
Other factors matter, of course. The monocultural and high trust (related variables) nature of Scandinavia also has an impact. But it is the level of official discretion which is key, with the level of banned transactions an accelerating factor since that then creates official discretions about enforcement plus major income source from transactions whose neither of whose participants want to attract state attention.