Downstream competition and profits under different input price bargaining structures

In a vertically related duopoly with input price bargaining, this paper re-examines the downstream firms’ profitability under different market competition degrees. It is shown the rather counterintuitive result that downstream firms earn highest profits with semi-collusion, whose level depends on the upstream bargaining structures, the relative parties’ bargaining power, and the parameters measuring the degree of product differentiation in the downstream market. Concerning social welfare, the key result is that policymakers can tolerate some degree of collusion with decentralized bargaining structures; centralized structures advise for a more procompetitive policy.

When to Lock the Volatile Input Price? Procurement of Commodity Components Under Different Pricing Schemes

Problem definition: We study a two-stage supply chain, where the supplier procures a key component to manufacture a product and the buyer orders from the supplier to meet a price-sensitive demand. As the input price is volatile, the two parties enter into either a standard contract, where the buyer orders just before the supplier starts production, or a time-flexible contract, where the buyer can lock a wholesale price in advance. Moreover, we consider three selling-price schemes: Market Driven, Cost Plus, and Profit Max. Academic/practical relevance: This problem is motivated by real practices in the cloud industry. Our model and optimization approach can address similar problems in other industries as well. Methodology: We assume that the input price follows a geometric Brownian motion. To determine the optimal ordering time, we propose an optimization approach that is different from the classic approach by Dixit et al. ( 1994 ) and Li and Kouvelis ( 1999 ). Our approach leads to deeper analytical results and more transparent ordering policy. Through a numerical experimentation, we compare profitability of different parties under different contracts, pricing schemes, and market conditions. Results: The buyer’s ordering policy is determined by a threshold policy based on the current time and input price; the optimal threshold depends on not only the drift and volatility of the input price but also, their relative magnitude. The supplier’s optimal procurement time should be determined by analyzing a trade-off between the holding cost of storing the components and the future input-price movement. Managerial implications: Under the Profit-Max and the Cost-Plus pricing schemes, the time-flexible contract is a Pareto improvement compared with the standard contract, whereas under the Market-Driven pricing scheme, the supplier may be better off under the standard contract. Moreover, although the most favorable scenario for the buyer is under the Profit-Max pricing scheme, the most favorable scenario for the supplier oftentimes is under the Cost-Plus pricing scheme. Furthermore, this study provides valuable insights into impacts of various characteristics of the component market, such as the trend and volatility of the input price, on the expected profit of the supply chain and its split between the two parties.

Location Choice of a Partially–Private Monopoly Supplier

This paper analyzes the location choice of an upstream monopolist who supplies input to asymmetric duopoly firms in a downstream market. The monopolist is partially private, in that it cares not only about its profit maximization but also about the survival of the downstream firms. Based on the Hotelling model, we find that the monopolist is always attracted to locate closer to the efficient downstream firm. In particular, when the efficiency difference between the two downstream firms is not too high, such that no firm is driven out of the market, the monopolist locates at a distance of 1/6 from the efficient firm in the line segment of unit length. Finally, considering the downstream firms’ survival, we show that the upstream monopolist charges a higher input price on the efficient firm. This study may be relevant to the product differentiation framework, in which firms can benefit from producing goods that are close to the preference of high-type consumers; to the pharmaceutical industry, in which pharmacy companies must cover a broad market segment; or to the policymaking process, in which policymakers may have an incentive to make a policy preferred by a particular group of the society. JEL Classifications: D42, L12, L230

GDP-PMI Nexus: Nigeria in Focus

This study seeks to contribute to extant literature on the relationship between the manufacturing and non-manufacturing purchasing manager’s index (PMI) and the real gross domestic product (GDP) in Nigeria. The study was carried out at Statistics Department, Central Bank of Nigeria, Abuja, Nigeria between 2010:Q1 – 2019:Q3 (for seasonally adjusted quarterly real gross domestic product (GDP)) and 2014:M7 – 2019:M9 (for monthly PMI). Pearson correlation test and plots are the adopted methods. The uniqueness of this study is the utilization of growth rates for both variables as well as employing a disaggregated approach in other to drill down to discover the true drivers of the relationship between the two variables. Results shows that CBN PMI is the most reliable of the three PMI indices computed for Nigeria. In addition, input price, output prices and quantity purchased, are the true determinants (from the manufacturing sector) of the direction of real GDP growth. Output price has a strong negative relationship with real GDP (-83%, contemporaneous), while input price too has a strong negative relationship with real GDP (-88% contemporaneous and -90% at lag 1) and quantity of purchases has a strong positive relationship with real GDP. From the non-manufacturing sector, average input price has a strong negative relationship with real GDP (-84%, with 2 periods lag), new export orders have a strong positive relationship with real GDP growth (77% with 3 periods lag) and imports also has a strong positive relationship with real GDP growth (85% with 1 period lag). Because prices have such a significant effect on GDP growth, it is recommended that both the monetary and fiscal authorities work together to curb inflation growth which has been trending upwards.

ANALYSIS OF CATTLE FARMER EXCHANGE RATE (NTP-T) AND THE FACTORS THAT INFLUENCE IT IN SIDOARJO REGENCY

Farmer Exchange Rate (NTP) is a proxy indicator or an indicator of the approach to the welfare level of breeders. The welfare of breeders can illustrate the purchasing power of farmers. The purpose of this study 1) To determine the level of welfare of cattle breeders and 2) To determine the effect of price index factors paid by farmers on the price index received by cattle breeders.This study uses NTP time series data with the base year 2012 = 100 as the basis for calculating the years 2018 - 2019. The location studied was determined by purposive sampling method in 5 districts in Sidoarjo Regency which are centers of beef cattle and dairy cows. The sample was selected by purposive random sampling as many as 75 cattle breeders. The NTP analysis method was carried out descriptively and the analysis of the factors that influenced the NTP was carried out using multiple linear regression. The results showed that the exchange rate of cattle farmers in Sidoarjo regency in 2019 increased by 1.81 percent from 109.41 in 2018 to 111.21 in 2019. This shows that cattle breeders in Sidoarjo district are experiencing a surplus or prosperity. The production input price index which includes the price of seeds, feed, and labor wages that must be paid by cattle breeders is a factor that has a significant effect on the cattle price index received by breeders.

Co-movement of commodity price indexes and energy price index: a wavelet coherence approach

This research sheds light on the causal link between commodity price indexes, i.e., the Agricultural Raw Materials Price Index, Industry Input Price Index, Metal Price Index, and Energy Price Index, in the global market, using wavelet coherence, Toda–Yamamoto causality, and gradual shift causality tests over the period 1992M1 to 2019M12. Findings from the wavelet power spectrum and partial wavelet coherence reveal that: (1) there was significant volatility in the Agricultural Raw Materials Price Index, Industry Input Price Index, Metal Price Index, and Energy Price Index between 2004 and 2014 at different frequencies; and (2) commodity price indexes significantly caused the energy price index at different time periods and frequencies. It is noteworthy that the outcomes of the Toda–Yamamoto causality and gradual-shift causality tests are in line with the results of wavelet coherence.