All about Payday Loans

Speedy payday loans are basically short term loans that have been designed to tide over people till their payday. The money is deposited directly into the bank account of the borrower. Usually, you have until payday to repay the loan. However, there are some lenders who will let you select the repayment period.

On the date of repayment, the lender takes the full amount that you owe along with the interest. They take it directly from your bank account. This will happen even if you need the money for paying essential bills like rent or mortgage, food, and heating.

Who are the People Using Payday Loans?

Anyone who has a checking account and a steady income can apply for a payday loan. However, it is more popular among borrowers who do not have access to the savings account or credit cards. As these loans do not require a credit check, people with credit problems or no credit at all can consider the option of payday loans. Recent immigrants and military personnel can also use payday loans.


Results of Credit Ratings and Speedy Payday Loans

 Banking RelationshipsThe empirical analysis procedures of this study are summarized in the following four parts. First, we use the t test and the nonparametric Wilcoxon rank sum methods to verify whether the mean or median of the banks with or without “WOBD” and “HCCL”, banks with four different types of ownership, and companies with high or low credit risk exhibit significant statistical differences in their characteristics. Then, we select publicly-held borrowing companies as empirical and control samples from banks with or without “WOBD” to test the impact of clients’ credit status and relationships on loan spreads under the regression model. We divide our clients with banks with or without WOBD as experimental samples and controlling samples and use the ordinary least squares empirical model to examine the factors impacting the loan spreads. The impacting factors include the financial attributes of banks and borrowing companies. In addition, we take the lending performance, ownership, banking relationship and the credit state (upgrade or downgrade) into consideration. As for understanding whether the loan policy-making process is just, we use the TCRI index to show the credit risk level of borrowing companies. Moreover, in this study we also include the interaction items of different credit systems and lending behavior to further explore the factors impacting the loan spread. In the third section, we apply the same method as in the second section except that the sample bank groups are changed to banks with or without “HCCL”. In the fourth section, we perform the robustness test by extending the empirical period to 2010 and discuss certain important variables in detail.



The following corollary states how prices of capital will differ across types of buyers, and how the sales revenue will vary with the discount factor.

Corollary: Under the conditions of Proposition 2, the average (undiscounted) price paid by sector A buyers is greater than the average (undiscounted) price paid by sector O buyers. Furthermore, a firm with a higher b will realize higher undiscounted proceeds from the sale of its equipment.

The implications of the model will be useful for interpreting the results we present later. The model also sheds light on several other results in the literature. For example, Shleifer and Vishny (1992) present several interesting anecdotes about how rapid sales of assets lead to price discounts. Pulvino (1997) shows that capital-constrained airlines not only sold their aircraft at lower prices, but were more likely to sell them to industry outsiders. Our model of thin resale markets for heterogeneous capital provides a straightforward explanation for these results. Searching for good match is a time-consuming process. If the firm does not spend the time, the capital ends up in lower valued matches and the firm receives less for its assets.


DISPLACED CAPITAL: Theoretical Framework 5

Proposition 1 establishes conditions under which there will be two stages to the selling process. Consider Figure 1, which shows graphs of VO(n) and VA(n) against n. Note that time moves backwards as n increases, since higher n means that the firm has more units left to sell. The two conditions together guarantee that VO(n) and VA(n) cross, and that there is at least one crossing where VA(n) crosses VO(n) from below. If the conditions hold, the first stage of the selling process involves some search for sector A buyers, which we call the “private liquidation sale.” The second stage involves selling all remaining units at once to sector O. We call this stage the “public auction.” If it is the case that VA(n) is less than VO(n) for all n<N, then the firm will skip the first stage and only hold the public auction.


DISPLACED CAPITAL: Theoretical Framework 4

Despite the higher costs of selling within the sector, the firm may choose to sell to other firms within the sector if the expected returns are large enough. Once the match is achieved, we make the common simplifying assumption that the selling price is equal to the valuation of the buyer. The valuations of the buyers, RA for insiders and RO for outsiders, are given as follows:
The f ’s are marginal revenue product shifters for each of the industries. For example, a decline in the demand for aerospace goods would be represented as a decline in fA. The S functions denote the goodness of the match of the capital’s characteristics, and are intended to capture the specificity of capital discussed above.8 Even within the same industry, capital from one firm may not be a perfect match for another firm. We assume that the value of a match with another industry insider rises with the selection currently available for sale, n. As shown above in equation (3), we also assume that it is always the case that the characteristics of the capital will be better suited to industry insiders than industry outsiders. If, however, fA falls far enough relative to fO then Ra can fall below RO.


DISPLACED CAPITAL: Theoretical Framework 3

Our assumption about costly search and matching is related to the large literature on search and matching (e.g. Stigler (1961), McCall (1970), Diamond (1982), Pissarides (1985), Mortenson (1986)). The structure of our model, however, contains a feature not found in other search models (to our knowledge.) In our model, the firm sells multiple units, whose value depends on the total selection available. This feature leads the firm to face a tradeoff between selling early at a low price and preserving the selection available to high-valuation buyers.

For those readers who wish to skip the theoretical details of the model, we briefly summarize the theoretical results to which we allude later in the empirical section. We show that under certain conditions, a firm structures its capital sales to consist of two parts. The first part, which is called the “private liquidation sale,” is a period of search for industry insiders. These sales result in high value matches and a higher sales price for the capital. The second part is a “public auction,” which involves a large auction in which the remaining capital is sold all at once to industry outsiders. The amount of capital sold to insiders is positively related to the firm’s discount factor: more patient firms spend more time searching for high quality matches among industry insiders.


DISPLACED CAPITAL: Theoretical Framework 2

This story, which will be formalized below, contains several key assumptions. We begin by motivating the first assumption of sectoral specificity of capital. We view each piece of capital as comprising a certain set of physical characteristics. When new capital is built for sale to a specific sector, it will have the best match of features for that sector. Despite the specificity of these characteristics, capital can be reallocated across sectors. The key is that only some of the characteristics of a particular piece of capital will have value in another sector.

We illustrate this idea with an example of a wind tunnel. A low-speed wind tunnel capable of producing winds from 10 to 270 miles per hour was sold to a company outside of the aerospace industry (San Diego Union-Tribune Oct. 23, 1994). This company rents the wind tunnel for $900 an hour to businesses such as bicycle helmet designers and architects who wish to gauge air flows between buildings. Most of the users require only low wind speeds and do not value the fact that the tunnel can produce 270 mile per hour wind speeds. Thus, a key characteristic of this wind tunnel – high air speeds – has no value outside of aerospace.


DISPLACED CAPITAL: Theoretical Framework

Allowing for capital specificity may also shed light on worker reallocation. Nadiri and Rosen (1969) demonstrated the importance of spillover effects of adjustment costs of one factor of production onto the behavior of another. If job creation and destruction are intimately linked with capital creation and destruction, then consideration of the specificity of capital may increase our understanding of the results of Davis and Haltiwanger (1990, 1992). Moreover, slow capital mobility may change the predicted effects of sectoral shocks. The lack of positive comovement between unemployment and vacancies has been taken as evidence against the hypothesis that sectoral shifts are an important contributor to aggregate fluctuations (e.g. Abraham and Katz (1986), Blanchard and Diamond (1989)). If, however, capital is required to create a vacancy, then a sectoral shift may not manifest itself as an increase in vacancies in the short-run. http://www.speedy-payday-loans.com/



Thus, to answer these questions it was necessary to construct a new data set. We collected confidential information from auctions of equipment from three large Southern California aerospace plants that discontinued operations. We then used information on sales prices and the characteristics of buyers to determine the extent of capital mobility for this particular industry. We will argue below that the aerospace industry is particularly interesting because it has undergone significant downsizing. review



Declining industries, worker layoffs, and factory closings are unavoidable consequences of a continuously evolving market economy. How efficiently does the market reallocate factors of production to productive uses in other sectors? Much is known about the outcomes for labor. Studies, such as those by Topel (1990), Ruhm (1991), Jacobson, LaLonde and Sullivan (1993), and Schoeni et al (1996), estimate the effects of reallocation on individual workers. They find that displaced workers often experience prolonged periods of unemployment, as well as significant losses in permanent income even after they become re-employed. These results suggest that labor market frictions, such as inefficient separations, search costs or industry-specific human capital, may be impediments to the efficient reallocation of labor.
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Relatively little is known, however, about the post-displacement outcomes for the other major factor of production – physical capital. Much capital is highly specialized, both in its embodied technology and factor substitution possibilities and in the types of products it can produce. While a substantial amount of theoretical and empirical work on investment behavior has analyzed the effects of costly reversibility on the decision to invest, little direct evidence has been offered on the efficiency with which capital is reallocated across firms and sectors.

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