Earn more, spend more, want more:
It does seem many people lose focus on happiness and instead focus on buying more things. This is something that I believe is a problem.
For $7.93 an Hour, It’s Worth a Trip Across a State Line
When the lowest pay rises, what happens?
No kidding. Other effects are a bit trickier but that one is not tough to figure out.
It is true jobs can be lost but at low rates that effect is very small. As the unemployment rate rises the job losses would increase with similar raises in the minimum wage. Raising the minimum wage to $7.25 now is a good idea – it should have been raised earlier.
I make $6.50 an hour. Am I poor? by Karen Datko:
I am no longer proud.
Pride should not be tied to how much money you have. It is, often, but it shouldn’t be. If you act foolishly or you waste money or you act irresponsibly being ashamed is possibly reasonable. When you have extra money, you can waste some and not feel ashamed because you have some to waste. But when you are doing your best you should be proud no matter how much money you have. Buying more pairs of shoes, or fancy coffee or a new video game or the full cable TV package… is not what you should take pride in.
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Economic statistics, like all data, needs to be defined. The way to collect data (economic data or any other type) is to operationally define the terms. Statistics don’t lie. Statistics can be faulty, when those collecting the data fail to use good operational definitions and the data quality is poor (without a definition people make guess…). People can also just make up false number. And people can try to mislead by stating statistics in a way that seem to indicate something that is not the most accurate way to view the whole situation.
The way to cope with such problems is to understand statistics and data. The data can be wrong. So you have to access that possibility. And the data can mean something different than you assume (and often the data is not presented with the operation definitions). When that is the case be careful about your assumptions (with financial and economic data and other data too). But don’t decide to just ignore data because then you condemn yourself to ignorance of the many things which data shed light onto.
In, What ‘Unemployment’ Really Means These Days, the unemployment data is explored. The post does a good job of showing how you can get different measures of the “unemployment rate” depending on how you define what you will measure. I happen to believe the existing measure is best but you need to understand that it doesn’t factor in underemployment and people giving up completely… I believe the best way to deal with those weaknesses is to have supplementary measures that enhance your understanding of the unemployment rate. And too view it as only one measure of economic health. Look also at median wages, health care coverage, hours worked, vacation time…
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In an instant, retirement savings vanish by Bob Sullivan:
This risk is something the government should address. The risk is to the economy at large, as well as having extreme consequences for individual investors. We need to do as much as possible to encourage retirement savings. Not providing government backing (such as provided by FDIC…) is a mistake. The funding should be similar to that for FDIC where member banks are assessed fees to cover the costs of the program based on the risks seen in that institution.
FDIC has done a great job of creating an environment that gives individuals confidence in the system and encourages economic development. Securities Investor Protection Corporation is another possible model but for something so important to the economic security of the country (and individuals lives) direct government involvement makes sense to me.
From the official US Federal Trade Commission site:
Viewing your credit report is an important step to financial security. You should review your credit reports annually (at least) to correct and any errors. Also doing so can be a tool to help you spot identity theft. The credit report site also has a large frequently asked question section with answers to questions like: What is a credit score? How do I request a “fraud alert” be placed on my file? Should I order all my credit reports at one time or space them out over 12 months? (I would suggest spreading the requests out during the year myself).
Friday Entrepreneurs: Premal Shah, Kiva.org
The usual loan terms are 12 months and over the course of your loan, you’ll receive periodic repayments which you can then re-invest in another entrepreneur or withdraw. In addition, you receive real business updates on the entrepreneur you’ve sponsored. So far, we’ve had a 100% repayment rate and we’re expecting at least a 96% repayment rate over time.
We think of Kiva as facilitating a kind of ‘grassroots capitalism’ — people here in the U.S. lending – not donating – a small amount to low income entrepreneurs in the developing world. For the low income entrepreneur, small amounts like $25 or $100 can provide the working capital needed to explode their small business growth, create a sustainable livelihood and enable them to repay you as an investment partner.
As I have said before, I really like helping people help themselves.
re: Myths of Manufacturing Productivity
Output counted should only measure the value added – it should not count the entire value (not the same thing exactly but similar – when a HDTV is sold by the plant to a wholesaler and then the wholesaler sells it to a retailer and then the retailer sells it to a customer the economic data does not add those 3 purchases together to get the total value of HDTV sales). The measures are suppose to be the amount added at the point of measure. So the output of the local plant does not count the total value of say the car but the value added at the plant. Obviously, like with most economic measures, this data has plenty of room for error.
While they intend to measure the added value as far, this is not easy and there can be reasons to distort the data (taxes, bonuses…). The VAT, used in Europe, is helpful illustration (both of the concepts and some of the measurement difficulties).
I keep looking for better data (I am actually surprised how sparse the data is given the importance). I would not want to make economic policy with the very incomplete data I have been able to find. Still, my belief is real global manufacturing output is up. And global manufacturing jobs are down. If those statements are right, productivity increase is the only reason – by definition.
When trying to look at country specific measures it does get more difficult – to find data that is obviously clear. Still, based on the data I have been able to find it seems that the USA continues to increase manufacturing output and decrease jobs. This seems right to me though I do agree the data I have seen still leaves questions. Previous posts I have made on the topic include: Manufacturing Value Added Economic Data – Manufacturing Jobs Data USA, China and globally, even manufacturing jobs data can include data quality issues but it is probably cleaner than most of the rest of this data. The data from this Clemson study shows the USA has lost a lower percentage of jobs than most every other country – Global Manufacturing Data by Country
Global data sources certainly still has data quality issues but you can be reasonably certain huge double counting is not going on. If so you would see the global totals increasing hugely. If a GM car was manufactured with 50% Mexican parts and the GM counted 100% of the value and Mexico counted there value then you would have 150% of the total value counted. Which would then mean the global figures would be counted not just increased output but also going up as the countries “over-counted” their output. And remember, in this example Mexican output could include (40% of their 50%) from Brazil…