We adopt a micro, partial equilibrium approach and consider a firm that operates under inflationiary expectations. Following Arrow (1962), we assume that the firm possesses a monopoly power that allows it to set the nominal price of its output or, alternatively, the price of one of its inputs. The firm produces a nonstorable product whose demand depends on its price relative to the price of rival commodities considered as an aggregate. The firm expects the aggregate price level and its costs of production to increase at a certain given rate. In the absence of adjustment costs the optimal policy would be to increase its own price continually at the same rate. We assume, however, that a fixed real cost is associated with each price change (Barro, 1972). Consequently, the optimal policy is characterized by a sequence of finite intervals during which the nominal price is held constant, followed by discrete price adjustments (Scarf, 1959). The analysis focuses on the effect of the expected rate of inflation on the frequency and the magnitude of these price changes.
The forecasting equations show that the estimated parameters of the state variables in equation (24) are in most cases significant and are able to explain 50%, 78% and 60% of the variance of the inflation rate in the aggregate, processed food and services sector calibrations respectively. These results imply that using higher order moments might be justified for the forecasting equation. It should be noted however, that as we assume that firms know the current value of inflation rate when choosing current prices, the forecasting equation can be expected to have only limited effects on their decision, so adding new variables and obtaining better fit can be expected to have limited effect on our results.
Abstract. In this paper, we have developed a fuzzy inventory model for deteriorating items with price and time dependent demand considering inflation effect on the system. Shortages if any are allowed and partially backlogged with a variable rate dependent on the duration of waiting time up to the arrival of next lot. The corresponding problem has been formulated as a nonlinear constrained optimization problem, all the cost parameters are fuzzy valued and solved. A numerical example has been considered to illustrate the model and the significant features of the results are discussed. Finally, based on these examples, a sensitivity analyses have been studied by taking one parameter at a time keeping the other parameters as same.
c o n s u m p t i o n , in o t h e r w o r d s e x p e n d i t u r e s m i n u s total t r a d i n g c o s t s w i t h this l a t t e r v a l u e b e i n g th e s u m of t r a n s a c t i o n s a n d s t o r a g e costs. G i v e n th e a d d i t i o n a l a s s u m p t i o n s th a t th e h o u s e h o l d r e c e i v e s all of its p a y m e n t s a t t he b e g i n n i n g of e a c h period, p o s s e s s e s p e r f e c t f o r e s i g h t a n d s p e nd s all of its i nc o m e in a s t e a d y s t ream, it is a s i m p l e m a t t e r to p ut i n t o g r a p h i c a l f o r m the t i m e p a t h s of t h e real h o l d i n g s of b o n d s a n d m o n e y as w e l l as c o m m o d i t i e s . A n e x a m p l e w i t h n c = 8 a n d ng = 2 is p r o v i d e d in F i g u r e 1 b elow. Th e r e a d e r s h o u l d n ot e t h a t t h e s y m b o l g r e p r e s e n t s re a l g o v e r n m e n t s a n d c s ta n ds for real c o n s u m p t i o n u n i t s in the p r e s e n t w o r k w h i l e g r e p r e s e n t s g o o d s a n d b b o n d s in t h e F - H a na l y s i s .
In a forward-looking environment, policy makers and market participants are constantly in search of indicators that might help predict future inflation. A wide range of measures of the state of the labour market – such as the gap between the actual and the natural level of unemployment, indicators of excess demand and of labour supply shortages – belong to the standard set of variables monitored by monetary authorities and analysts. In this context, a group of indicators that generally receives substantial attention is the one related to workers’ compensa- tions: changes in wages, labour productivity and unit labour costs. The under- lying assumption is that wage dynamics play a central role in determining price developments. In particular, if nominal wages increase faster than productivity does, price stability is jeopardised because companies are faced with growing pro- duction costs and will eventually be forced to increase their prices. According to this view, appropriate measures of labour cost developments at the aggregate level can be useful as early detectors of future inflation.
The DSGE model is estimated using Bayesian techniques. The findings favor the dual wage stickiness model over the baseline model based on only Calvo-type wage stickiness. First, although households reset their wages at certain intervals of time, estimates of the parameter associated with the quadratic costs of wage adjustment are significantly different from zero, rejecting the null hypothesis of no quadratic wage adjustment costs. Second, the marginal likelihood clearly supports the dual wage stickiness model over the baseline model, which relies only on Calvo-type wage stickiness (Calvo 1983). The inclusion of quadratic wage adjustment costs yields a substantial improvement of the model in fitting the data. Third, the observed dynamic correlation between wage inflation and real output can be better replicated under dual wage stickiness. While the baseline model fails to generate the expected lead-lag relationship between wage inflation and output, the introduction of quadratic costs of wage adjustment in the proposed model yields the observed negative (positive) relationship between past (future) wage inflation and real output. The dual wage stickiness model is able to explain the fact that a rise in current output is associated with a subsequent increase in wage inflation. Overall, the presence of dual sticky wage stickiness helps provide an improved explanation of wage inflation dynamics.
Figure 4 shows the estimated impulse responses of inflation, unemployment, output, and steel tariff rate to steel tariff shocks, together with the 16th and 84th percentile error bands. The main results are the following. A positive steel tariff shock triggers an increase in steel tariff rate, a rise in inflation, an increase in unemployment, and a decline in real output. The responses of inflation and unemployment to the steel tariff shock are consistent with the steel tariff-driven stagflation hypothesis. Since steel-consuming industries constitute an integral part of U.S. economy, the price inflation that follows the steel tariff shock could result from steel-consuming industries attempting to pass the increased steel costs to the consumers. The extent to which they succeed in doing so can be inferred from the short-run price elasticity of demand for consumer goods. To determine the economy-wide short-run price elasticity of demand for consumer goods, an autoregressive distributed lag (ARDL) model is estimated with personal consumption expenditures as dependent variable and consumer price index and real disposable personal income as explanatory variables. The estimation yielded a price elasticity of -0.903 indicating that, the short-run demand for consumer goods is inelastic which in turn suggests that steel-consuming industries have a small but a possible window of passing some of its costs to consumers. A price elasticity of -1 or higher would have ruled out this possibility. 2
The ideological ‘normalisation’ of homeownership (Gurney 1999b), not least in terms of increasing homeownership rates (which nonetheless have fallen since 2004), deregulation of the private rental sector and increased stigmatisation of social housing, has been paralleled by a significant growth in house values, indeed everywhere (Piketty 2014). Figure 1 shows historic movements in homeownership rates and house prices in the UK. Notwithstanding volatility, UK house price inflation averaged 6.5% over the last 50 years, which represented 2.5% percentage points above general price inflation. Figure 1 also shows that if house prices had only risen by inflation since 1970, the average national house price would have currently been £67,400 rather than £188,000. Likewise, if we take 2000 as year of reference, which is also the time since house prices have skyrocketed, the corresponding figure would have been £123,900. While there is lively debate on the macroeconomic effects of this sharp increase in aggregate housing wealth (e.g. greater ‘feel good’ consumption; the collateral outcome), there is agreement regarding its increasingly unequal distribution across households, having
important role in successful operation of any organization. The project is said to be successful if it is completed on desired time and cost. The construction project delays are the major problems in public and private works. Delays frequently occurs in the life time of the construction projects and it cause cost overrun of the planned cost. Some major factors such as bad or inclement weather due to heavy rains and floods, scope changes, environmental protection and mitigation costs, schedule delay, strikes, technical challenges, inflation and local government pressures also causes of cost escalation. The escalation clauses provided in contracts are a means to cover unexpected costs resulting from the fluctuations in the prices for raw materials, fuels and labour during the construction project. By conducting surveys on some construction companies, it was found that the calculation for escalated cost is done manually. The aim of this study is to identify the causes and effects of cost escalation and schedule delays in the construction projects and to develop a software for calculating the escalated cost for entire project. This study also aims to analyse the benefits and obstacles of using computer applications for estimating the escalation of any construction projects.
Although widely accepted as a measure of the comparative lifetime costs of electricity generation alternatives, levelised cost of energy (LCOE) lacks a theoretical foundation in the academic literature and encompasses a number of areas where caution is important. Therefore, this paper seeks to provide a theoretical foundation by comparing the metric with alternative cost of energy metrics and by undertaking a brief literature review to describe its strengths and weaknesses. In comparison with other potential measures of unit cost of energy, LCOE is found to be the preferred choice, in large part because of its widespread adoption. The weaknesses of the LCOE are found to centre on discount rate, inflation effects and the sensitivity of results to uncertainty in future commodity costs. These weaknesses are explored in the context of comparing combined cycle gas fired gen- eration and offshore wind in the UK, based on publicly available cost measures. It is found that with variability of future fuel gas prices, and a Monte Carlo approach to modelling LCOE, the range of LCOE for CCGT is much broader in comparison to the LCOE of offshore wind. It is urged that explicit account be taken of the areas of weakness in future use of LCOE.
12 For this positive inflation shock, the real exchange rate immediately adjusts to the higher inflation. Consequently, real monetary conditions become tighter and the output gap slightly drops, and the economy is adjusting through demand (see Figure 2). In fact, the lower output gap decreases the real marginal costs which reduce inflationary pressures and leads to looser monetary conditions, mainly through a second-round real exchange rate appreciation. Here too, the central bank does not have to use the nominal interest rate to react to the inflationary pressure or to the output drop because the adjustment is done through the real exchange rate mechanism.
5.3.1 Productivity in the Consumption and Investment-Good Sector of Production Expectations of future productivity gains generate boom-bust dynamics in GDP, consumption, hours, investment and house prices. See figure 15. The intuition is as follows. Expectations of higher productivity in the future lead households to increase their current consumption expenditure. Due to demand pressures, inflation increases. At the same time, the anticipation of higher productivity in the future generates expectations of higher future housing prices. The decline in the current real rate coupled with higher expected housing prices lead to an increase in Borrowers’ housing expenditure and indebtedness. Given the presence of limits to credit, impatient households increase their labor supply in order to raise internal funds for housing investment. Due to capital adjustment costs, firms already begin adjusting the stock of capital when news about a future reduction in the policy rate spread. For the increase in business investment to be coupled with an increase in total hours worked, wages must rise. The increase in business and housing investment makes GDP increase already at the time of the signal. A four-period anticipated increase in productivity generates a boom in housing prices, housing investment, consumption, GDP, hours and indebtedness. The peak response of all aggregate variables corresponds to the time in which expectations realize. After that all variables slowly return to their initial values. In contrast, if expectations do not realize there is a more substantial drop in both quantities and prices (solid line). See Appendix C for robustness analysis to different parameter values.
Christiano, Ilut, Motto, and Rostagno (2008) show that a standard one-sector real business cycle model with habit persistence and costs of adjusting the flow of investment generates a boom-bust pattern in output, consumption, investment and hours in response to news on productivity that do not materialize. The price of capital, however, is negatively correlated with all other aggregate variables and therefore it falls and then increases. The introduction of an inflation targeting central bank and sticky nominal wages make the price of capital co-move with the other aggregate variables and boom-bust dynamics emerge. When news spreads about a future increase in productivity, aggregate variables increase including hours worked. The increase in hours is possible because the real wage falls, hence producers are willing to raise labor demand. Since nominal wages are sticky, a decrease in real wages occurs because prices fall faster than wages. The inflation-targeting central bank responds to this fall in inflation by cutting the nominal interest rate, which in turn raises investment and the price of capital. Two features are crucial for boom-bust dynamics in the model of Christiano et al.: sticky nominal wages and wages stickier than prices.
Thus, as shown in equation , the first 3 variables are gross domestic product rate for healthcare and medicine sector (GDPH), inflation in the pharmaceutical sector (INFD), and free-market currency exchange rate (EX). The variable of interest (TEP) and the collection period of quests for pharmaceutical companies (VOSOL) are ordered 4th and 5th as these variables are fast-moving compared to policy variables but slow-moving compared to macro variables. The block policy variables include healthcare cost (HE), money volume (M1), and interest rates. The government mostly pays healthcare costs; therefore, it can be regarded as the fiscal policy variable. Due to the presence of fiscal dominance in the Iranian economy , money volume and interest rate are con- sidered as monetary policy variables that are ordered after fiscal variables . Equation  shows the relation between reduced-form residuals and structural shocks of the system, with A − 1 in a lower-triangular shape.
influence the economy of a country domestically and international level. Previous studies proposing a negative relationship between stock costs and expansion. Chakravarty et al, (2010) visualize that high inflation predicts a financial downturn and keeping in view this the organizations begin auctioning off their stock. An increment in the supply of stock then diminishes the stock costs. Since stocks mirror firms' future gaining potential a normal monetary downturn prompts firms to auction the money related stocks and in this way high expansion and low stock costs have a tendency to go together (Rostagno et al, 2010). Erikiet al (2001) also cited that there is negative relationship between stock prices and inflation. However, Bhattacharya and Mukherjee (2002) demonstrated a two-path causation between stock cost and the rate of expansion, while file of mechanical creation lead the stock cost. Then again, a positive relationship is additionally conceivable in the middle of expansion and stock costs as startling inflation raises the organizations' value esteem in the event that they are net borrower (Kessel, 1956; Ioannidis et al., 2005).
During the past decades, supplier selection has grown in importance as a strategic issue in the area of supply chain management [1-3]. The supplier selection process was traditionally affected by different intangible and tangible criteria such as technical capability, service level, price, and quality [4, 5]. The emergence of sustainability over the past few decades has witnessed increasing interest from practitioners and academia in the field of sustainable supplier selection [6, 7]. Hence, many organizations have begun to emphasize on considering environmental, social, and economic dimensions of sustainability in their supplier selection processes by adapting sustainable supply chain creativities [8, 9]. According to the studies in the literature, the perception is that there are three important decisions related to supplier selection. These three decisions are concerned with the kind of products to be ordered, the quantities required, and when they are required [10, 11]. These three decisions make order lot- sizing and supplier selection closely related. Lot-sizing problems contain the objective of determining the period in which an order should take place and the quantities to be ordered to satisfy demand while minimizing costs . One of the critical factors that can affect a buyer’s decisions and the lot-size of each product is the inflation rate. The effect of inflation has become a constant characteristic and a very important issue in several developing economies, especially in the third world countries . Considering the effect of inflation on lot-sizing can reduce the total cost of purchasing over the planning horizon. Since the inflation rate leads to an increase in products prices, it can harm companies that do not consider this issue