Felix Salmon and Kevin Drum discuss counterfeit luxury goods and their effect on sales of the real items. However they overlook one type of damage. Kevin Drum:
... There are also people who just flatly can't afford a real Gucci and never will. But in those cases Gucci isn't losing anything when they buy a fake. ...
But this is surely wrong. People buy luxury goods in part to show off, to flaunt their wealth. However this is ineffective if there are lots of indistinguishable cheap fakes in circulation. So Gucci is hurt by cheap fakes as they diminish the appeal of the real thing. Similarly luxury brands are wary of adding low end items to their product line. It cheapens the brand as the saying goes.
I can understand why people think enforcing laws against counterfeiting luxury goods should be low priority but luxury good makers are not crazy to want these laws enforced.
Sunday, December 6, 2009
Saturday, December 5, 2009
Why housing
Kevin Drum asks why we had a housing bubble and concludes:
The real difference seems to lie not in housing becoming a better target for investment, but in real goods and services becoming less attractive ones. ...
But this seems wrong. There was a complete collapse of underwriting standards for housing loans. So it was very easy to speculate in housing with other people's money. This made housing a more attractive target for speculative investment than other areas where loans were harder to get meaning you were required to risk more of your own money. So there was a flood of borrowed money into housing which drove up prices which attracted still more investment. A classic asset price bubble. You don't need easy credit for an asset price bubble but it certainly helps.
Matthew Yglesias agrees but then adds:
All that said, it’s worth emphasizing that the mere existence of an asset-price bubble and its subsequent collapse doesn't necessarily lead to a years-long recession. A worse policy response than the one we got could have saddled us with Depression conditions, but a better one could have avoided a ton of the human suffering we’re seeing right now.
Of course an asset price bubble doesn't have to cause major problems if it is small and isolated. But this asset bubble was allowed to grow to the point where it endangered the solvency of many big banks and other financial institutions. Once that has occurred there is likely no easy way out. It is unlikely of course that the policy response was perfect but I don't see any obvious way to have avoided our present problems. Yglesias has consistently claimed more can and should be done but that seems to me to be mostly wishful thinking.
The real difference seems to lie not in housing becoming a better target for investment, but in real goods and services becoming less attractive ones. ...
But this seems wrong. There was a complete collapse of underwriting standards for housing loans. So it was very easy to speculate in housing with other people's money. This made housing a more attractive target for speculative investment than other areas where loans were harder to get meaning you were required to risk more of your own money. So there was a flood of borrowed money into housing which drove up prices which attracted still more investment. A classic asset price bubble. You don't need easy credit for an asset price bubble but it certainly helps.
Matthew Yglesias agrees but then adds:
All that said, it’s worth emphasizing that the mere existence of an asset-price bubble and its subsequent collapse doesn't necessarily lead to a years-long recession. A worse policy response than the one we got could have saddled us with Depression conditions, but a better one could have avoided a ton of the human suffering we’re seeing right now.
Of course an asset price bubble doesn't have to cause major problems if it is small and isolated. But this asset bubble was allowed to grow to the point where it endangered the solvency of many big banks and other financial institutions. Once that has occurred there is likely no easy way out. It is unlikely of course that the policy response was perfect but I don't see any obvious way to have avoided our present problems. Yglesias has consistently claimed more can and should be done but that seems to me to be mostly wishful thinking.
Coupons
Bed, Bath and Beyond has inundated me with coupons providing 20% off on any single item. As a result I am reluctant to buy more than one thing at a time in the local store. Somehow this does not seem like the optimal marketing strategy.
Thursday, December 3, 2009
Value Line Fund
Thursday I called the Value Line 800 number and told them to exchange all my shares in the Value Line Fund for shares in the Value Line Income and Growth Fund. I had initially invested equal amounts in both with a series of small purchases in 1982-1983. I have been reinvesting all distributions ever since.
The investment in the Value Line Fund was not one of my better calls. Although the value did increase by more than a factor of 5, an annual return of about 6.3%, this considerably lagged the market. The performance in recent years seemed particularly bad. And indeed according to Morningstar (via Quicken ) over the last 5 years 99% of similar mutual funds have performed better. Since I also had a large unrealized capital loss selling seemed indicated.
Perhaps I should have gotten out of the other Value Line fund as well but it had done considerably better. Its value had increased by more than a factor of 12, an annual return of about 9.7%. This still lagged the market (but perhaps with less risk). And according to Morningstar over the last 5 years only 4% of similar funds have done better. Since exchanging just meant a phone call and a complete redemption would have required a signature guarantee my natural laziness and inertia dictated exchanging.
Looking back at the performance of my investments over time it is a bit disconcerting how much luck is involved. Since I tend to take the path of least resistance and let investments ride rather casual initial decisions can have big consequences over time as differences in performance accumulate.
The investment in the Value Line Fund was not one of my better calls. Although the value did increase by more than a factor of 5, an annual return of about 6.3%, this considerably lagged the market. The performance in recent years seemed particularly bad. And indeed according to Morningstar (via Quicken ) over the last 5 years 99% of similar mutual funds have performed better. Since I also had a large unrealized capital loss selling seemed indicated.
Perhaps I should have gotten out of the other Value Line fund as well but it had done considerably better. Its value had increased by more than a factor of 12, an annual return of about 9.7%. This still lagged the market (but perhaps with less risk). And according to Morningstar over the last 5 years only 4% of similar funds have done better. Since exchanging just meant a phone call and a complete redemption would have required a signature guarantee my natural laziness and inertia dictated exchanging.
Looking back at the performance of my investments over time it is a bit disconcerting how much luck is involved. Since I tend to take the path of least resistance and let investments ride rather casual initial decisions can have big consequences over time as differences in performance accumulate.
Wednesday, December 2, 2009
Recent comments broken
The recent comments gadget has stopped working. I don't think this was because of anything I did. A brief internet search suggests the gadget is a bit flaky. Hopefully the problem will resolve itself soon.
Pension started
Back in September I sent in all the paperwork required to start my pension on November 1. You might think this would be soon enough to get my first payment on time but it seems it wasn't. I didn't receive anything until Wednesday when I was paid for November and December. Fortunately the delay didn't matter for me but people who need the first payment on time should make sure they get all the paperwork done well in advance.
My pension is a small fraction of what I was being paid but it does look a bit better on a net basis since a smaller percentage is being taken out. On the other hand I will have to start paying my own medical insurance next year. Still the pension amount will be adequate for me to live on (although if inflation is high it may not remain so). If you are well paid (as I was) it isn't really necessary to match (or nearly match) your previous income for a satisfactory retirement. I find the benefit of not working to be worth quite a bit.
My pension is a small fraction of what I was being paid but it does look a bit better on a net basis since a smaller percentage is being taken out. On the other hand I will have to start paying my own medical insurance next year. Still the pension amount will be adequate for me to live on (although if inflation is high it may not remain so). If you are well paid (as I was) it isn't really necessary to match (or nearly match) your previous income for a satisfactory retirement. I find the benefit of not working to be worth quite a bit.
Tuesday, December 1, 2009
Predicting rare events
One final comment on "The Black Swan" .
Taleb is correct that it is difficult to confidently say much based on empirical data about events that occur too rarely to appear in your data set. However I don't really agree that this means you shouldn't even try. There are techniques that help a bit and that may provide useful warnings. The following example comes from a talk I heard many years ago at IBM.
Suppose you are trying to predict the 200 year flood or 500 year flood, the maximum flow for some river that can be expected over the stated period, and you only have say 100 years of data. You can look at the maximum flows each year and model them as the results of some underlying random distribution and then derive the expected n-year flood. But this is risky as the real distribution may include occasional samples from a process which didn't happen to operate during the period for which you have empirical data. A real world example is where hurricanes occasionally pass over the watershed in question. If your data set does not include any hurricane years you may get a completely misleading picture of what the maximum flood size over periods of time long enough to include hurricane years is likely to be. But there is something you can do. As well as looking at historical data from the particular watershed you are forecasting you can look at data from many similar watersheds. In this case some of these watersheds would have experienced hurricanes giving you notice that a process capable of generating extreme events likely operates occasionally for your particular watershed as well. This will make your predictions more realistic and may encourage more prudent behavior.
This technique is generalizable. For example for financial markets you can look at data from outside the United States. Of course this just mitigates the underlying problem and you may still be caught by surprise but it isn't really practical to worry about everything. I agree with Taleb that you should expect the occasional surprise but not that it is useless to even try to predict and avoid them.
Taleb is correct that it is difficult to confidently say much based on empirical data about events that occur too rarely to appear in your data set. However I don't really agree that this means you shouldn't even try. There are techniques that help a bit and that may provide useful warnings. The following example comes from a talk I heard many years ago at IBM.
Suppose you are trying to predict the 200 year flood or 500 year flood, the maximum flow for some river that can be expected over the stated period, and you only have say 100 years of data. You can look at the maximum flows each year and model them as the results of some underlying random distribution and then derive the expected n-year flood. But this is risky as the real distribution may include occasional samples from a process which didn't happen to operate during the period for which you have empirical data. A real world example is where hurricanes occasionally pass over the watershed in question. If your data set does not include any hurricane years you may get a completely misleading picture of what the maximum flood size over periods of time long enough to include hurricane years is likely to be. But there is something you can do. As well as looking at historical data from the particular watershed you are forecasting you can look at data from many similar watersheds. In this case some of these watersheds would have experienced hurricanes giving you notice that a process capable of generating extreme events likely operates occasionally for your particular watershed as well. This will make your predictions more realistic and may encourage more prudent behavior.
This technique is generalizable. For example for financial markets you can look at data from outside the United States. Of course this just mitigates the underlying problem and you may still be caught by surprise but it isn't really practical to worry about everything. I agree with Taleb that you should expect the occasional surprise but not that it is useless to even try to predict and avoid them.
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