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"Penelitian ini bertujuan untuk "melihat seberapa besar pengeluaran pembangunan mempengaruhi perekonomian khususnya indikator-indikator ekonomi makro pada model ekonomi makro triwulanan di Indonesia".Metode analisis yang digunakan adalah model ekonometri, yaitu model persamaan simultan, dengan 8 persamaan (yang terdiri dari persamaan identitas dan persamaan tingkah laku). Hipotesa yang ingin dibuktikan adalah:1. PDB=Cg+Cp+PMTB +CIS+X-M2. CP =ao+a₁PDB+a2 CP­ ₁+e₁ PDB dan CP­ ₁ mempunyai hubungan positif dengan CP, artinya bahwa jika PDB dan CP­ ₁ naik maka Konsumsi swasta akan naik, dan begitu juga sebaliknya.3. CG =bο+b1 PDB+b2 CG­ ₁ +e2PDB dan CG­ ₁ berhubungan positif dengan CG, artinya bahwa jika PDB dan CG­ ₁ naik maka Konsumsi pemerintah akan naik, dan sebaliknya jika CG turun.4. PMTB = cο+c1 PDB-c2 KI +c3GDE+c4FDI +c5 PMTB + e3 Hubungan antara PDB, GDE dan FDI serta PMTB­ ₁ dengan PMTB adalah positif yang berarti bahwa jika PDB, GDE, dan FDI naik maka nilai PMTB akan naik dan sebaliknya jika PMTB turun, sedangkan hubungan PMTB dengan KI adalah negatif artinya jika KI naik, maka akan menurunkan PMTB.5. X =dQ+dY PDB+d2 XCR-d3 EXPTAX+d4 X+e4Hubungan antara PDB, XCR Ekspor periode sebelumnya dengan Ekspor adalah positif yang menunjukkan bahwa jika PDB, XCR, dan X­ ₁, naik maka nilai ekspor barang dan jasa akan naik dan begitu juga sebaliknya, sedangkan hubungan X dengan EXPTAX adalah negatif artinya jika pajak ekspor naik, maka akan menurunkan ekspor.6. M =f0+f1 PDB-f2 XCR- f3 IMPTAX +f4 M+esHubungan antara PDB dan M­ ₁ dengan Impor adalah positif yang menunjukkan bahwa jika PDB dan M­ ₁ naik maka nilai impor barang dan jasa akan naik dan begitu juga sebaliknya, sedangkan hubungan M dengan XCR dan IMPTAX adalah negatif artinya jika nilai tukar rupiah menguat dan pajak impor naik, maka akan menurunkan impor.7. KI =go+g1 PDB+g2RSBI -g3 NM +e₆Hubungan antara PDB dan RSBI dengan Suku bunga kredit investasi adalah positif yang menunjukkan bahwa jika PDB dan RSBI naik maka KI akan naik dan jika RSBI turun maka akan menurunkan KI, sedangkan hubungan NM dengan KI adalah negatif artinya jlka jumlah uang beredar (Ml) naik, maka akan menurunkan KI.8. FDI = ha + hl PDB + h2 XCR + h3 KI + e₇ Hubungan antara PDB dan XCR dengan KI adalah positif yang menunjukkan bahwa jika PDB, Kurs, dan KI naik maka Penanaman Modal Asing akan naik, begitu juga sebaliknya.Hasil simulasi dengan model persamaan di atas, adalah:1. Kebijakan pengeluaran pembangunan mempengaruhi beberapa indikator ekonomi makro tersebut yaitu: PDB, PMTB (Investasi), Penanaman Modal Asing, Konsumsi Pemerintah dan Swtasta, Ekspor dan Impor Barang dan Jasa, serta Suku Bunga Kredit Investasi.2. Skenario 1 yang merupakan modifikasi dari Propenas merupakan skenario terbaik karena menambah persentase pengeluaran pembangunan terhadap PDB dengan bertahap."

"Through analysis of the European Union Emissions Trading Scheme (EU ETS) and the Clean Development Mechanism (CDM), this book demonstrates how to use a variety of econometric techniques to analyze the evolving and expanding carbon markets sphere, techniques that can be extrapolated to the worldwide marketplace. It features stylized facts about carbon markets from an economics perspective, as well as covering key aspects of pricing strategies, risk and portfolio management."

"[This book provides a state-of-the art overview on the major approaches in high-frequency econometrics, including univariate and multivariate autoregressive conditional mean approaches for different types of high-frequency variables, intensity-based approaches for financial point processes and dynamic factor models. It discusses implementation details, provides insights into properties of high-frequency data as well as institutional settings and presents applications to volatility and liquidity estimation, order book modelling and market microstructure analysis.;This book provides a state-of-the art overview on the major approaches in high-frequency econometrics, including univariate and multivariate autoregressive conditional mean approaches for different types of high-frequency variables, intensity-based approaches for financial point processes and dynamic factor models. It discusses implementation details, provides insights into properties of high-frequency data as well as institutional settings and presents applications to volatility and liquidity estimation, order book modelling and market microstructure analysis., This book provides a state-of-the art overview on the major approaches in high-frequency econometrics, including univariate and multivariate autoregressive conditional mean approaches for different types of high-frequency variables, intensity-based approaches for financial point processes and dynamic factor models. It discusses implementation details, provides insights into properties of high-frequency data as well as institutional settings and presents applications to volatility and liquidity estimation, order book modelling and market microstructure analysis.]"

"[This tutorial presents a hands-on introduction to a new discrete choice modeling approach based on the behavioral notion of regret-minimization. This so-called Random Regret Minimization-approach (RRM) forms a counterpart of the Random Utility Maximization-approach (RUM) to discrete choice modeling, which has for decades dominated the field of choice modeling and adjacent fields such as transportation, marketing and environmental economics. Being as parsimonious as conventional RUM-models and compatible with popular software packages, the RRM-approach provides an alternative and appealing account of choice behavior. Rather than providing highly technical discussions as usually encountered in scholarly journals, this tutorial aims to allow readers to explore the RRM-approach and its potential and limitations hands-on and based on a detailed discussion of examples. , This tutorial presents a hands-on introduction to a new discrete choice modeling approach based on the behavioral notion of regret-minimization. This so-called Random Regret Minimization-approach (RRM) forms a counterpart of the Random Utility Maximization-approach (RUM) to discrete choice modeling, which has for decades dominated the field of choice modeling and adjacent fields such as transportation, marketing and environmental economics. Being as parsimonious as conventional RUM-models and compatible with popular software packages, the RRM-approach provides an alternative and appealing account of choice behavior. Rather than providing highly technical discussions as usually encountered in scholarly journals, this tutorial aims to allow readers to explore the RRM-approach and its potential and limitations hands-on and based on a detailed discussion of examples. ]"